CN113657325A - Method, apparatus, medium, and program product for determining annotation style information - Google Patents
Method, apparatus, medium, and program product for determining annotation style information Download PDFInfo
- Publication number
- CN113657325A CN113657325A CN202110974826.8A CN202110974826A CN113657325A CN 113657325 A CN113657325 A CN 113657325A CN 202110974826 A CN202110974826 A CN 202110974826A CN 113657325 A CN113657325 A CN 113657325A
- Authority
- CN
- China
- Prior art keywords
- attribute
- information
- target
- labeling
- target entity
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 57
- 238000002372 labelling Methods 0.000 claims abstract description 96
- 238000004590 computer program Methods 0.000 claims description 11
- 238000003908 quality control method Methods 0.000 claims description 7
- 230000004044 response Effects 0.000 claims description 2
- 238000013473 artificial intelligence Methods 0.000 abstract description 5
- 239000003814 drug Substances 0.000 abstract description 4
- 238000003058 natural language processing Methods 0.000 abstract description 2
- 206010011224 Cough Diseases 0.000 description 28
- 238000012545 processing Methods 0.000 description 14
- 206010047924 Wheezing Diseases 0.000 description 11
- 238000004891 communication Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 10
- 238000005516 engineering process Methods 0.000 description 8
- 238000012015 optical character recognition Methods 0.000 description 5
- 208000037656 Respiratory Sounds Diseases 0.000 description 4
- 230000003993 interaction Effects 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 201000010099 disease Diseases 0.000 description 3
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 230000006698 induction Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 208000024891 symptom Diseases 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 230000033228 biological regulation Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 229940079593 drug Drugs 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 230000007704 transition Effects 0.000 description 2
- 238000011282 treatment Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 229930186147 Cephalosporin Natural products 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000002924 anti-infective effect Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000003115 biocidal effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 229940124587 cephalosporin Drugs 0.000 description 1
- 150000001780 cephalosporins Chemical class 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000005713 exacerbation Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 230000007721 medicinal effect Effects 0.000 description 1
- 230000003924 mental process Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 230000002085 persistent effect Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 230000001953 sensory effect Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000001225 therapeutic effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Computer Vision & Pattern Recognition (AREA)
- General Physics & Mathematics (AREA)
- Artificial Intelligence (AREA)
- Physics & Mathematics (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Medical Informatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computing Systems (AREA)
- Mathematical Physics (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The present disclosure provides a method, an apparatus, a medium, and a program product for determining annotation style information, which relate to the field of artificial intelligence such as natural language processing and smart medicine. One embodiment of the method comprises: acquiring a medical record text; identifying the medical record text to obtain target relation information between a target entity in the medical record text and each attribute in at least one attribute; and determining corresponding labeling style information according to the target relation information and the relative position between each attribute and the target entity, wherein the labeling style information is used for labeling the target relation information.
Description
Technical Field
The present disclosure relates to the field of computers, and more particularly, to natural language processing and smart medicine, and more particularly, to a method, apparatus, medium, and program product for determining annotation style information.
Background
The medical record is the record of the medical activities of the medical staff for examining, diagnosing and treating the occurrence, development and outcome of the diseases of the patients, and is the medical health file of the patients which is obtained by summarizing, arranging and comprehensively analyzing the acquired data and writing the data according to the specified format and requirements. With the development of computer and internet technologies, most hospitals realize the electronization of clinical medical records, and the electronic medical records are medical records recorded, stored, managed, transmitted and reproduced by electronic equipment, and have the advantages of safety, reliability, convenience in recording, storing, sharing and the like.
At the present stage, valuable and available information can be extracted from the electronic medical record by performing big data analysis on the electronic medical record so as to obtain key information which needs to be searched by medical staff.
Disclosure of Invention
The embodiment of the disclosure provides a method, a device, a medium and a program product for determining labeling style information.
In a first aspect, an embodiment of the present disclosure provides a method for determining annotation style information, including: acquiring a medical record text; identifying the medical record text to obtain target relation information between a target entity in the medical record text and each attribute in at least one attribute; and determining corresponding labeling style information according to the target relation information and the relative position between each attribute and the target entity, wherein the labeling style information is used for labeling the target relation information.
In a second aspect, an embodiment of the present disclosure provides an apparatus for determining annotation style information, including: a text acquisition module configured to acquire a medical record text; the text recognition module is configured to recognize the medical record text to obtain target relation information between a target entity in the medical record text and each attribute in the at least one attribute; and the style determining module is configured to determine corresponding labeling style information according to the target relation information and the relative position between each attribute and the target entity, wherein the labeling style information is used for labeling the target relation information.
In a third aspect, an embodiment of the present disclosure provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method as described in the first aspect.
In a fourth aspect, the disclosed embodiments propose a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method as described in the first aspect.
In a fifth aspect, the disclosed embodiments propose a computer program product comprising a computer program that, when executed by a processor, implements the method as described in the first aspect.
According to the method, the device, the medium and the program product for determining the labeling style information, firstly, a case history text is obtained; then identifying the medical record text to obtain target relationship information between a target entity in the medical record text and each attribute in at least one attribute; and finally, determining corresponding labeling style information according to the target relationship information and the relative position between each attribute and the target entity, wherein the labeling style information is used for labeling the target relationship information. The corresponding labeling style information can be determined based on the target relationship information between the target entity and at least one attribute in the medical record text and the relative position between the attribute and the target entity, so that the labeling of the target relationship information between the target entity and the attribute is realized, and the target relationship information between the target entity and the attribute can be accurately acquired.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
Other features, objects, and advantages of the disclosure will become apparent from a reading of the following detailed description of non-limiting embodiments which proceeds with reference to the accompanying drawings. The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is an exemplary system architecture diagram in which the present disclosure may be applied;
FIG. 2 is a flow diagram of one embodiment of a method for determining annotation style information in accordance with the present disclosure;
FIG. 3 is a flow diagram of one embodiment of a method for determining annotation style information in accordance with the present disclosure;
FIGS. 4(a) to 4(d) are schematic diagrams illustrating the annotation style information;
FIG. 5 is a schematic diagram of an application scenario of a method for determining annotation style information according to the present disclosure;
FIG. 6 is a schematic structural diagram illustrating an embodiment of an apparatus for determining annotation style information according to the present disclosure;
FIG. 7 is a block diagram of an electronic device used to implement an embodiment of the disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
It should be noted that, in the present disclosure, the embodiments and features of the embodiments may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 illustrates an exemplary system architecture 100 to which embodiments of the method for determining annotation style information or the apparatus for determining annotation style information of the present disclosure may be applied.
As shown in fig. 1, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user can use the terminal devices 101, 102, 103 to interact with the server 105 over the network 104 to receive medical history text and the like. The terminal devices 101, 102, 103 may have installed thereon various client applications, intelligent interactive applications, such as image processing applications, text processing applications, and so on.
The terminal apparatuses 101, 102, and 103 may be hardware or software. When the terminal devices 101, 102, and 103 are hardware, the terminal devices may be electronic products that perform human-Computer interaction with a user through one or more modes of a keyboard, a touch pad, a touch screen, a remote controller, voice interaction, or handwriting equipment, such as a PC (Personal Computer), a mobile phone, a smart phone, a PDA (Personal Digital Assistant), a wearable device, a PPC (Pocket PC, palmtop), a tablet Computer, a smart car machine, a smart television, a smart speaker, a tablet Computer, a laptop Computer, a desktop Computer, and the like. When the terminal apparatuses 101, 102, 103 are software, they can be installed in the above-described electronic apparatuses. It may be implemented as multiple pieces of software or software modules, or as a single piece of software or software module. And is not particularly limited herein.
The server 105 may provide various services. For example, the server 105 can obtain medical history text; identifying the medical record text to obtain target relation information between a target entity in the medical record text and each attribute in at least one attribute; and determining corresponding labeling style information according to the target relation information and the relative position between each attribute and the target entity, wherein the labeling style information is used for labeling the target relation information.
The server 105 may be hardware or software. When the server 105 is hardware, it may be implemented as a distributed server cluster composed of a plurality of servers, or may be implemented as a single server. When the server 105 is software, it may be implemented as multiple pieces of software or software modules (e.g., to provide distributed services), or as a single piece of software or software module. And is not particularly limited herein.
It should be noted that the method for determining the annotation style information provided by the embodiment of the present disclosure is generally performed by the server 105, and accordingly, the apparatus for determining the annotation style information is generally disposed in the server 105.
It should be understood that the number of electronic devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of electronic devices, networks, and servers, as desired for implementation.
With continued reference to FIG. 2, a flow 200 of one embodiment of a method for determining annotation style information in accordance with the present disclosure is illustrated. The method for determining annotation style information may include the steps of:
In this embodiment, an execution subject (e.g., the server 105 shown in fig. 1) of the method for determining annotation style information may acquire a medical record text. The medical record text can be a text in the medical record data, and the type of the medical record data can be an image or a text.
Here, the medical record information may include symptoms, diseases, names of medicines, and the like. Medical record text is obtained from medical record data by Optical Character Recognition (OCR) techniques or OCR Recognition models.
The OCR recognition model can be a model obtained by training medical record texts and recognition results of the medical record texts as training samples.
In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations and do not violate the good customs of the public order.
In an embodiment, the executing subject may identify a medical record text to obtain a target entity in the medical record text and at least one attribute having target relationship information with the target entity; target relationship information between the at least one attribute and the target entity is then determined. The target entity may be an entity in the medical field, and the target entity may include: diseases, symptoms, drugs, examinations, signs, treatments, etc. The above attributes may be set by a practitioner with medical experience in combination with business requirements, and may include: location, time of occurrence, duration, frequency, size, amount, degree, predisposition, exacerbation factors, alleviation factors, nature, color, odor, status, stage/type, dosage, efficacy, mode of administration, therapeutic effect, test description, and the like. The target relationship information may be used to characterize the relationship between the target entity and each attribute. For example, the target relationship information between the target entity and the attribute is the occurrence frequency. The target entity can be at least one entity in the medical record text.
Correspondingly, in this example, identifying the medical record text to obtain the target entity and the corresponding at least one attribute in the medical record text may include: identifying the medical record text through Natural Language Understanding (NLU) to obtain an identification result of the medical record text; and then, determining a target entity and at least one attribute corresponding to the target entity in the medical record text through a preset table, wherein the preset table comprises the target entity and the corresponding attribute, and the attribute table can be generated through published books and/or related medical files. Or, the medical record text is identified through an OCR identification model to obtain an identification result of the medical record text; and then, determining a target entity in the medical record text and at least one attribute corresponding to the target entity through a preset table.
It should be noted that after obtaining the target relationship information between the target entity and the attribute, the structured medical record can be generated.
In this embodiment, the execution body may determine the annotation style information according to the target relationship information and the relative position between each attribute of the at least one attribute and the target entity. The above-mentioned relative position may be a position between the position information of each attribute on the screen of the electronic device and the position information of the target entity on the screen of the electronic device.
Here, the annotation style information may be used to annotate the target relationship information between the target entity and each attribute by annotating lines and/or annotating text.
The method for determining the labeling style information provided by the embodiment of the disclosure comprises the steps of firstly acquiring a medical record text; then identifying the medical record text to obtain target relationship information between a target entity in the medical record text and each attribute in at least one attribute; and finally, determining corresponding labeling style information according to the target relationship information and the relative position between each attribute and the target entity, wherein the labeling style information is used for labeling the target relationship information. The corresponding labeling style information can be determined based on the target relationship information between the target entity and at least one attribute in the medical record text and the relative position between the attribute and the target entity, so that the labeling of the target relationship information between the target entity and the attribute is realized, and the relationship information between the target entity and the attribute can be accurately acquired.
With further reference to fig. 3, fig. 3 illustrates a flow 300 of another embodiment of a method for determining annotation style information in accordance with the present disclosure. The method for determining annotation style information may include the steps of:
In the present embodiment, an execution subject (e.g., the server 105 shown in fig. 1) of the method for determining annotation style information may determine a relative position between each attribute and the target entity according to the position information of each attribute of the at least one attribute.
Specifically, the relative position between each attribute and the target entity can be determined according to each attribute in the medical record text and the position information of the target entity on the screen of the server (e.g., the server 105 shown in fig. 1).
In one example, the location information of the target entity and attribute may be determined by offsetLeft and offsetTop. The relative position of the target entity and the attribute can then be determined by the difference between the offset left and offset top of the target entity and the attribute.
And step 304, determining the labeling style information according to the target relation information and the corresponding relative position of each attribute.
In this embodiment, the execution body determines the annotation style information according to the target relationship information and the relative position corresponding to each attribute.
Here, a mapping relationship between the labeling style information and the relative positions corresponding to the target relationship information and each attribute may be established in advance to determine the labeling style information according to the relative positions corresponding to the target relationship information and each attribute. The labeling style information may be used to label target relationship information between each attribute and the target entity. The annotation style information can comprise annotation lines and/or annotation texts. The style presentation form of the annotation style information may include static display, dynamic display, and the like.
In this embodiment, the specific operations of steps 301 and 302 have been described in detail in steps 201 and 202, respectively, in the embodiment shown in fig. 2, and are not described again here.
As can be seen from fig. 3, compared with the embodiment corresponding to fig. 2, the method for determining annotation style information in the present embodiment highlights the step of determining the annotation style information. Thus, the solution described in this embodiment determines the relative position between each attribute and the target entity according to the position information of each attribute in the at least one attribute and the position information of the target entity; then determining the information of the marking style according to the target relation information and the corresponding relative position of each attribute; the corresponding labeling style information can be determined based on the relative position determined by the position information of each attribute in the at least one attribute and the position information of the target entity and the target relationship information, so that the labeling of the target relationship information between the target entity and the attribute is realized, and the relationship information between the target entity and the attribute can be accurately acquired.
In some optional implementations of this embodiment, determining the relative position between each attribute and the target entity according to the position information of each attribute in the at least one attribute and the position information of the target entity may include:
determining at least one attribute in the medical record text and position information of a target entity on a preset screen according to the size information of the preset screen; and determining the relative position between each attribute and the target entity according to the position information of each attribute and the position information of the target entity.
In this implementation manner, the execution subject may determine, according to the size information of the preset screen, position information of each attribute and the target entity in the medical record text on the preset screen; and then, determining the relative position between each attribute and the target entity according to the position information of each attribute and the position information of the target entity. The preset screen may be a screen of a server (e.g., the server 105 shown in fig. 1), and the preset screen is used for displaying a medical record text. According to the size information of the preset screen, the display arrangement of the medical record texts on the preset screen can be determined, for example, the medical record texts are displayed on the preset screen for 3 lines.
In this implementation manner, when the size information of the preset screen changes, the method for determining the annotation style information may further include:
determining the relative position between the attribute and the target entity according to the new size information, and re-determining the labeling style information; or, before the size information of the preset screen is changed (for example, after step 203 is executed), acquiring the image of the annotation style information, so that when the size information of the preset screen is changed, the image of the annotation style information is displayed on the screen corresponding to the new size information.
In one example, after the size information of the preset screen is changed, new size information may be listened through window.
In this implementation manner, the execution subject may determine, according to the persistent information of the preset screen, the position information of each attribute information in the at least one attribute in the medical record text and the position information of the target entity, and determine the relative position between each attribute and the target entity.
In some optional implementations of this embodiment, the annotating style information may include: labeling text and/or labeling lines.
In this implementation manner, the label text may be used to show the target relationship information between each attribute and the target entity. The annotation text may include at least one of: font size, color, character spacing of text. The above-mentioned labeling line may connect each attribute and the target entity through a line, and the labeling line may include a line type (for example, a dotted line or a solid line or a transparent line or a line with an arrow), a line width, a line color, and the like.
Here, the labeling text is used for labeling the target relationship information, and the labeling line is used for pointing to the attribute and the target entity corresponding to the target relationship information.
In one example, in fig. 4(a), the annotation text is used to annotate the target relationship information (i.e., 'occurrence frequency') between 'cough (i.e., target subject)' and 'recurrence', the annotation line is used to point to 'cough' and 'recurrence', and the arrow of the annotation line points to 'cough'.
It should be noted that the display effect of the label text and the label line can be set according to the requirement of the user or the size information of the screen.
In this implementation manner, the target relationship information between each attribute and the target entity may be labeled according to the labeling text and/or the labeling line included in the labeling style information.
In some optional implementation manners of this embodiment, if the annotation style information includes an annotation text and an annotation line, the annotation text includes at least one of the following items: and marking the position information of the text on the marking line and the distance between the texts.
The labeling line may include: the system comprises a line starting point and a line ending point, wherein the line starting point is used for pointing to each attribute, and the line ending point is used for pointing to a target entity.
It should be noted that the labeling text may be in any direction of the labeling line, for example, in any position above, below, and the like of the labeling line; or, the label text is displayed on the label line.
In this implementation, the target relationship information between the attribute and the target entity may be labeled through a labeling line and a labeling text.
In some optional implementations of the embodiment, the annotation text may include at least one of: marking the position information of the text, the space of the text and the font information of the text.
In this implementation, the location information of the annotation text may be the location information of the annotation text on a preset screen (e.g., the screen of the server 105 shown in fig. 1). The spacing of the annotation text can be the spacing between characters in the annotation text. The font type information of the label text may include the font type, color, height of the label text equal to the font-related information.
In this implementation manner, the height of the labeling text may be lower than the height of the labeling line, so as to avoid overlapping the labeling text and the labeling line.
In some optional implementations of this embodiment, the annotation line may include a line start point and a line end point, where the line start point may be used to point to each attribute, and the line end point may be used to point to the target entity; or the start of the link may be used to point to the target entity and the end of the link may be used to point to each attribute.
In this implementation manner, the attribute and the target entity corresponding to a certain labeling text can be determined by the direction of the labeling line.
In the implementation manner, the attributes and the target entities with corresponding relations can be embodied through the direction of the marking lines.
In some optional implementations of this embodiment, the annotation line may further include a first inflection point, and the annotation text is displayed in a preset direction of the first inflection point.
In this implementation, the annotation text is displayed in a preset direction of the first inflection point of the annotation line, for example, the annotation text is displayed above, below, left, right, or any other position of the first inflection point.
In this implementation, the execution body may display the annotation text in a preset direction of a first inflection point of the annotation line.
In some optional implementations of this embodiment, the annotation line may further include a first inflection point and a second inflection point, and the annotation text is displayed in a preset direction along a line connecting the first inflection point and the second inflection point.
In this implementation manner, the annotation text may be displayed in a preset direction of a connection line between the first inflection point and the second inflection point, for example, the annotation text is displayed above, below, to the left, to the right, or at any other position of the connection line between the first inflection point and the second inflection point.
It should be noted that the corner of the annotation line at the first inflection point and the second inflection point can be any angle, and the annotation line can be included in the scope of the embodiments of the present disclosure as long as the annotation line does not overlap with the medical record text. Optionally, the corner of the marking line at the first inflection point and/or the second inflection point is 90 degrees.
In FIG. 4(a), the annotation text is displayed above the line connecting the first inflection point and the second inflection point, the corner of the first inflection point and the second inflection point being 90 degrees. In the 4(a), the attribute is displayed on the same line of the preset screen as the target entity, and the target relationship information includes that the target relationship information between 'repeat' and 'cough' is 'occurrence frequency', '10 years' and 'cough' is 'time', 'emphasis' and 'cough' are 'return state', '3 days' and 'cough' are 'return time', where 'occurrence frequency', 'time', 'return state', 'return time' are annotation texts. In this 4(a), the lines of notation between 'repeat, 10 years, aggravation, 3 days' and 'cough' point from 'repeat, 10 years, aggravation, 3 days' to 'cough', respectively; the arrow on the marked line points to 'cough'.
In fig. 4(b), the attributes and target entities are displayed in different lines of a preset screen (e.g., the screen of the server 105 shown in fig. 1).
In this fig. 4(b), 'cough (i.e., target entity)' and '2006' have target relationship information of 'time'; the target relationship information between 'cough' and 'after getting cold from spring' is 'induction condition'; the target relationship information between 'cough' and 'relapse' is 'frequency of occurrence'; the target relationship information between 'cough' and 'bulk' is 'degree'; the target relationship information between 'cough' and 'after cephalosporin antibiotic administration' is 'outcome condition'; the target relationship information between 'cough' and 'gradual symptom relief' is 'outcome status'.
It should be noted that, if the attribute is on the target entity or in the same row as the target entity, the attribute is used as the starting point of the connection line of the labeling line, moves upward, moves laterally to the upper side of the target entity, and finally points to the target entity. If the attribute is below the target entity, the attribute is used as a connection starting point of the marking line, moves upwards to the upper part of the line, moves transversely to the lower part of the target entity and finally points to the target entity.
In fig. 4(c), the medical record text is displayed on a preset screen (e.g., the screen of the server 105 shown in fig. 1) in 3 lines, wherein the target entity is displayed on line 2.
In this fig. 4(c), the target relationship information between 'wheeze (i.e., target entity)' and 'fall 2006' is 'time'; the target relationship information between 'wheezing' and 'after catching cold' is 'induction conditions'; the target relationship information between 'wheeze' and 'after activity' is 'transfer condition'; the target relationship information between 'wheeze' and 'emphasis' is 'transition state'; the target relationship information between 'wheezing' and 'after anti-infective treatment' is 'outcome condition'; the target relationship information between 'wheeze' and '1 month' is 'relegation time'; the target relationship information between 'wheezing' and 'gradual release' is 'transition state'.
It should be noted that, if the attribute is in a row on the target entity or in the same row as the target entity, the attribute is used as a starting point of a connection line of the labeling line, moves upward, moves laterally to above the target entity, and finally points to the target entity. If the attribute is in the next line of the target entity, the attribute is used as the starting point of the connecting line of the marking line, moves upwards to the upper part of the line, moves transversely to the lower part of the target entity and finally points to the target entity.
In fig. 4(d), the medical record text is displayed on a preset screen (e.g., the screen of the server 105 shown in fig. 1) in 2 lines, wherein the target entity is displayed on line 2.
In this fig. 4(d), the target relationship information between 'wheeze (i.e., target entity)' and '12 months 2010' is 'time'; the target relationship information between 'wheezing' and 'after catching cold' is 'induction conditions'; the target relationship information between 'wheeze' and 'reappearance' is 'frequency of occurrence'; the target relationship information between 'wheeze' and 'apparent cough' is 'accompanying state'.
It should be noted that the attribute is used as a starting point of a connection line of the labeling line, moves upward, moves laterally to above the target entity, and finally points to the target entity.
In this implementation manner, the annotation text can be displayed in the preset direction of the connection line between the first inflection point and the second inflection point of the annotation line.
In some optional implementation manners of this embodiment, if at least two attributes included in the at least one attribute are displayed on the preset screen in the same row, heights of the annotation lines corresponding to each of the at least two attributes on the preset screen are different.
In this implementation manner, the execution main body may display the annotation line corresponding to each of the at least two attributes on a preset screen according to a preset height corresponding to the attribute.
It should be noted that the preset height may be set according to the size information of the preset screen and/or the requirement of the user.
In this implementation manner, in order to avoid overlapping of the labeling lines corresponding to the multiple attributes, the labeling line corresponding to each attribute in the multiple attributes may be displayed at a different height.
In some optional implementations of the embodiment, a height of the callout bar corresponding to each of the at least two attributes on the preset screen is a product of a display order of each attribute on the preset screen and the preset height.
In this implementation manner, the execution body may determine the height of the corresponding annotation line according to a product of a display order of each of the at least two attributes on the preset screen and a preset height.
In one example, each of the at least two attributes is numbered in the display order of the case history text on the preset screen, with index starting at 1. The height of the marking line is determined by the product of lineHeight and index in options, so that layered display of the marking line can be realized, and the connecting lines are prevented from being overlapped.
Correspondingly, in 4(a), 'repeat', '10 years', 'weight', '3 days' correspond to different heights of the labeled lines, and the heights of the labeled lines are 1 × lineHeight, 2 × lineHeight, 3 × lineHeight, and 4 × lineHeight, in this order.
It should be noted that lineHeight can be the height of each line of text in the medical record text, or randomly set by the user.
In addition, the height of the labeling text can be smaller than the height of the corresponding labeling line.
In this implementation manner, in order to avoid overlapping of the labeling lines corresponding to the multiple attributes, the labeling line corresponding to each attribute in the multiple attributes may be displayed at a different height.
In some optional implementations of this embodiment, the method for determining annotation style information further includes: acquiring preset relationship information; and responding to the situation that the target relation information does not accord with the preset relation information, and displaying the advice quality control prompt information.
In this implementation manner, the execution main body may obtain the preset relationship information, so as to display the order quality control prompt information when the target relationship information is inconsistent with the preset relationship information.
In one example, the 'cough' target relationship information corresponding to '10 remaining years' is 'transfer condition'; the preset relationship information corresponding to 'cough' and '10 remaining years' is 'time'. At the moment, the target relation information is inconsistent with the preset relation information, and the advice quality control prompt information is displayed. For example, 'go-back condition' highlight, red color display, etc.; or the text reminding target relation information is inconsistent with the preset relation information; or the voice reminding target relation information is inconsistent with the preset relation information.
In the implementation mode, the target relation information between the target entity and the attribute in the case history text can be accurately marked, so that the accuracy of quality control of the medical advice is improved.
In some alternative implementations of the present embodiment, the annotation lines and annotation text can be drawn through inline elements (span tags) or SVG.
Here, the Span tag is located inside the Span tag of the attribute, the Span tag of the attribute is relatively located, and the embedded element is absolutely located. In the process of drawing the marking line by the Span label, the starting point of the connecting line of the marking line is absolutely positioned relative to the attribute, and the position of the starting point of the connecting line does not need to be repeatedly determined.
Here, the annotation line and the annotation text may be drawn by Scalable Vector Graphics (SVG). The SVG can be used to handle graphics class requirements. For relatively complex visual graphics, attribute relation labeling can be realized on the SVG canvas by embedding the canvas on the original element. The SVG can decouple the marking text and the marking lines, and is beneficial to the maintenance of projects.
In one example, a callout line can be drawn through a "span" label: from the line indicated by the attribute, the source is above the left side of the attribute, and the height is the product of lineHeight and index in options.
It should be noted that js can draw a connecting line between the attribute and the body by the method of createlement and apendchild. The starting point of the connecting line is the position on the left side of the attribute, and the end point is the position on the left side of the body.
In the implementation mode, the starting point of the marking line is absolutely positioned relative to the attribute, and the position of the starting point of the marking line does not need to be determined repeatedly.
In one example, a line connecting the source and target (e.g., a line connecting a first inflection point and a second inflection point) may be plotted as follows.
Specifically, the left position of the cross-line connecting the source and target is affected by attributes on the left or right side of the target entity. When the attribute is on the left side of the target entity, the left coordinate of the connecting line is 0; when the attribute is on the right side of the target entity, the left coordinate of the connecting line is the absolute value of the distance of the negative attribute relative to the target entity. The position of Top is consistent with the calculation of height from the line indicated by the attribute, which is the product of lineHeight and index in negative options. The width of the link is the absolute value of the distance of the attribute relative to the target entity.
In one example, the label text on a horizontal line (e.g., a line connecting the first inflection point and the second inflection point) may be drawn as follows.
Specifically, the labeling text on the horizontal line is between the line source and the horizontal line of the target, and when the attribute is on the left side of the target entity, the left coordinate of the line is half of the absolute value of the distance between the attribute and the target entity; when the attribute is to the right of the target entity, the left coordinate of the link is half the absolute value of the distance of the negative attribute relative to the target entity. The top value of the text is slightly higher than the position of the cross line connecting the source and the target, and is the product of lineHeight and index in negative options plus a fixed height, for example 14 px.
In one example, a line pointing to a target entity (e.g., a line connecting a first inflection point (e.g., an inflection point near the end of a line) and the end of the line) may be drawn as follows.
Specifically, the left position of the line pointing to the target entity is affected by whether the attribute is to the left or right of the target entity. In addition, the height and bottom position of the line is affected by the attribute being on the top side (including the attribute and the target entity being in the same row) or the bottom side of the target entity.
In one example, an arrow pointing onto a callout line can be drawn as follows.
Specifically, the left position of the line pointing to the target entity is affected by whether the attribute is to the left or right of the target entity. In addition, the height and bottom position of the line is affected by the attribute being on the top side (including the attribute and the target entity being in the same row) or the bottom side of the target entity.
In some optional implementation manners of this embodiment, in order to enable the annotation text and the annotation line to be displayed on the preset screen without overlapping with the medical record text, the method for determining the annotation style information further includes: and setting the display requirement of the medical record text on a preset screen.
In one example, the display requirements may include at least one of:
(1) each line can display 5-12 attributes at most; (2) when the attribute is folded, drawing a marking line by taking the left side of the first character in the attribute as the starting point of a connecting line of the marking line; (3) the target entity attribute extraction area is set to a preset width, for example, 250 px.
In one example, the display requirements may further include: and the line spacing of the medical record text on a preset screen.
In this implementation, the layout of the first attribute of the line may be set as an inline-block (display). And calculating the line spacing according to the number of the marking lines between the two lines.
In the implementation mode, the determination of the labeling style information can be realized by determining the position information of the target main body and the attribute in the medical record text, so that the development cost is reduced. Furthermore, the method is simple.
With further reference to fig. 5, fig. 5 illustrates a schematic diagram of an application scenario of a method for determining annotation style information according to the present disclosure. In this application scenario, a user may click on selecting an entity (e.g., 'cough') in a medical record text displayed on a screen of a server 501 (e.g., the server 105 shown in fig. 1), and display annotation style information on the screen, the annotation style information being for annotating that the target relationship information entity between the entity and the corresponding at least one attribute has a corresponding relationship.
In fig. 5, after the 'cough' is selected, the following is displayed on the preset screen: the target relationship information between 'iteration' and 'cough' is 'occurrence frequency', 'time' between '10 years' and 'cough', 'attribution state' between 'emphasis' and 'cough', and 'attribution time' between '3 days' and 'cough', wherein 'occurrence frequency', 'time', 'attribution state', 'attribution time' are annotation texts. In this 4(a), the lines of notation between 'repeat, 10 years, aggravation, 3 days' and 'cough' point from 'repeat, 10 years, aggravation, 3 days' to 'cough', respectively; the arrow on the marked line points to 'cough'.
In the implementation mode, the annotation style information can be generated on a preset screen through a span label or SVG.
With further reference to fig. 6, as an implementation of the method shown in the above-mentioned figures, the present disclosure provides an embodiment of an apparatus for determining annotation style information, where the embodiment of the apparatus corresponds to the embodiment of the method shown in fig. 2, and the apparatus may be applied to various electronic devices in particular.
As shown in fig. 6, the apparatus 600 for determining annotation style information of the present embodiment may include: a text acquisition module 601, a text recognition module 602, and a style determination module 603. The text acquisition module 601 is configured to acquire a medical record text; a text recognition module 602 configured to recognize the medical record text to obtain target relationship information between a target entity in the medical record text and each attribute in the at least one attribute; a style determining module 603 configured to determine corresponding labeling style information according to the target relationship information and the relative position between each attribute and the target entity, wherein the labeling style information is used for labeling the target relationship information.
In the present embodiment, in the apparatus 600 for determining annotation style information: the detailed processing and the technical effects thereof of the information obtaining module 601, the requirement determining module 602, the weight determining module 603, and the result determining module 604 can refer to the related descriptions of step 201 and step 204 in the corresponding embodiment of fig. 2, and are not described herein again.
In some optional implementations of this embodiment, the style determining module 603 includes: a position determining unit configured to determine a relative position between each attribute and the target entity according to the position information of each attribute of the at least one attribute and the position information of the target entity; and the style determining unit is configured to determine the labeling style information according to the target relation information and the corresponding relative position of each attribute.
In some optional implementations of this embodiment, the position determination unit is further configured to: determining each attribute in the medical record text and the position information of the target entity on the preset screen according to the size information of the preset screen; and determining the relative position between each attribute and the target entity according to the position information of each attribute and the target entity on the preset screen.
In some optional implementations of this embodiment, the annotating style information includes: labeling texts and/or labeling lines; the labeling text is used for labeling the target relationship information, and the labeling line is used for pointing to the attribute and the target entity corresponding to the target relationship information.
In some optional implementations of this embodiment, the labeling line includes: and the marking text is displayed in the preset direction of the connecting line of the first inflection point and the second inflection point.
In some optional implementation manners of this embodiment, if at least two attributes included in the at least one attribute are displayed on the preset screen in the same row, heights of the annotation lines corresponding to each of the at least two attributes on the preset screen are different.
In some optional implementations of the embodiment, a height of the callout bar corresponding to each of the at least two attributes on the preset screen is a product of a display order of each attribute on the preset screen and the preset height.
In some optional implementations of this embodiment, the apparatus for determining annotation style information further includes: an information acquisition module configured to acquire preset relationship information; and the information display module is configured to display the medical order quality control prompt information in response to the target relation information not conforming to the preset relation information.
In some optional implementations of this embodiment, the apparatus for determining annotation style information further includes: and the generation style module is configured to generate the annotation style information on the preset screen by using the span label or the SVG.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
FIG. 7 illustrates a schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 7, the device 700 comprises a computing unit 701, which may perform various suitable actions and processes according to a computer program stored in a Read Only Memory (ROM)702 or a computer program loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other by a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
Various components in the device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, or the like; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.
Artificial intelligence is the subject of studying computers to simulate some human mental processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), both at the hardware level and at the software level. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing, and the like; the artificial intelligence software technology mainly comprises a computer vision technology, a voice recognition technology, a natural voice processing technology, machine learning/deep learning, a big data processing technology, a knowledge map technology and the like.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in this disclosure may be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions mentioned in this disclosure can be achieved, and are not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (21)
1. A method for determining annotation style information, comprising:
acquiring a medical record text;
identifying the medical record text to obtain target relationship information between a target entity in the medical record text and each attribute in at least one attribute;
and determining corresponding labeling style information according to the target relationship information and the relative position between each attribute and the target entity, wherein the labeling style information is used for labeling the target relationship information.
2. The method of claim 1, wherein the determining corresponding annotation style information according to the target relationship information and the relative position between each attribute and the target entity comprises:
determining a relative position between each attribute and a target entity according to the position information of each attribute in the at least one attribute and the position information of the target entity;
and determining the labeling style information according to the target relation information and the relative position corresponding to each attribute.
3. The method of claim 2, wherein the determining the relative position between each attribute of the at least one attribute and the target entity according to the position information of each attribute and the position information of the target entity comprises:
determining each attribute in the medical record text and position information of a target entity on a preset screen according to size information of the preset screen;
and determining the relative position between each attribute and the target entity according to the position information of each attribute and the target entity on the preset screen.
4. The method of any one of claims 1-3, wherein the annotating style information comprises: labeling texts and/or labeling lines; the labeling text is used for labeling the target relationship information, and the labeling line is used for pointing to the attribute and the target entity corresponding to the target relationship information.
5. The method of claim 4, wherein the labeling line comprises: the annotation text is displayed in a preset direction of a connecting line of the first inflection point and the second inflection point.
6. The method according to claim 4 or 5, wherein if at least two attributes included in the at least one attribute are displayed on the preset screen in the same row, the height of the annotation line corresponding to each of the at least two attributes on the preset screen is different.
7. The method of claim 6, wherein the height of the annotation line corresponding to each of the at least two attributes on the preset screen is the product of the display order of each attribute on the preset screen and the preset height.
8. The method of claim 1, further comprising:
acquiring preset relationship information;
and responding to the fact that the target relation information does not accord with the preset relation information, and displaying the quality control prompt information of the medical advice.
9. The method of claim 1 or 8, further comprising:
and generating the marked style information on a preset screen by using a span label or SVG.
10. An apparatus for determining annotation style information, comprising:
a text acquisition module configured to acquire a medical record text;
the text recognition module is configured to recognize the medical record text to obtain target relationship information between a target entity in the medical record text and each attribute in at least one attribute;
and the style determining module is configured to determine corresponding labeling style information according to the target relation information and the relative position between each attribute and the target entity, wherein the labeling style information is used for labeling the target relation information.
11. The apparatus of claim 10, wherein the pattern determination module comprises:
a position determining unit configured to determine a relative position between each attribute of the at least one attribute and a target entity according to the position information of each attribute and the position information of the target entity;
and the style determining unit is configured to determine the labeling style information according to the target relation information and the relative position corresponding to each attribute.
12. The apparatus of claim 11, wherein the location determination unit is further configured to:
determining each attribute in the medical record text and position information of a target entity on a preset screen according to size information of the preset screen;
and determining the relative position between each attribute and the target entity according to the position information of each attribute and the target entity on the preset screen.
13. The apparatus according to any one of claims 10-12, wherein the annotation style information comprises: labeling texts and/or labeling lines; the labeling text is used for labeling the target relationship information, and the labeling line is used for pointing to the attribute and the target entity corresponding to the target relationship information.
14. The apparatus of claim 13, wherein the annotation line comprises: the annotation text is displayed in a preset direction of a connecting line of the first inflection point and the second inflection point.
15. The apparatus according to claim 13 or 14, wherein if at least two attributes included in the at least one attribute are displayed on the preset screen in the same row, the height of the annotation line corresponding to each of the at least two attributes on the preset screen is different.
16. The apparatus of claim 15, wherein the height of the callout bar corresponding to each of the at least two attributes on the preset screen is a product of the display order of each attribute on the preset screen and the preset height.
17. The apparatus of claim 10, the apparatus further comprising:
an information acquisition module configured to acquire preset relationship information;
an information display module configured to display the medical order quality control prompt information in response to the target relationship information not conforming to the preset relationship information.
18. The apparatus of claim 10 or 17, further comprising:
and the generation style module is configured to generate the marked style information on a preset screen by using the span label or the SVG.
19. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-9.
20. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-9.
21. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110974826.8A CN113657325B (en) | 2021-08-24 | 2021-08-24 | Method, apparatus, medium and program product for determining annotation style information |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110974826.8A CN113657325B (en) | 2021-08-24 | 2021-08-24 | Method, apparatus, medium and program product for determining annotation style information |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113657325A true CN113657325A (en) | 2021-11-16 |
| CN113657325B CN113657325B (en) | 2024-04-12 |
Family
ID=78481785
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110974826.8A Active CN113657325B (en) | 2021-08-24 | 2021-08-24 | Method, apparatus, medium and program product for determining annotation style information |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113657325B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116522935A (en) * | 2023-03-29 | 2023-08-01 | 北京德风新征程科技股份有限公司 | Text data processing method, processing device and electronic equipment |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2004057458A2 (en) * | 2002-12-17 | 2004-07-08 | Terastat, Inc. | Method and system for dynamic visualization of multi-dimensional data |
| US20100306242A1 (en) * | 2009-05-30 | 2010-12-02 | Edmond Kwok-Keung Chow | Methods and Systems for Annotation of Digital Informatin |
| CN103970859A (en) * | 2014-04-29 | 2014-08-06 | 杨立法 | Google user map text labeling method based on SVG |
| CN110162779A (en) * | 2019-04-04 | 2019-08-23 | 北京百度网讯科技有限公司 | Appraisal procedure, device and the equipment of quality of case history |
| CN110968708A (en) * | 2019-12-20 | 2020-04-07 | 华中师范大学 | Method and system for labeling education information resource attributes |
| CN111460765A (en) * | 2020-03-30 | 2020-07-28 | 掌阅科技股份有限公司 | Electronic book labeling processing method, electronic equipment and storage medium |
| CN111767410A (en) * | 2020-06-30 | 2020-10-13 | 平安国际智慧城市科技股份有限公司 | Construction method, device, equipment and storage medium of clinical medical knowledge map |
| CN111814664A (en) * | 2020-07-07 | 2020-10-23 | 广联达科技股份有限公司 | Method and device for identifying marks in drawing, computer equipment and storage medium |
| CN111816311A (en) * | 2020-07-22 | 2020-10-23 | 北京捷通华声科技股份有限公司 | State identification method, system and device |
| CN112507090A (en) * | 2020-11-30 | 2021-03-16 | 北京百度网讯科技有限公司 | Method, apparatus, device and storage medium for outputting information |
| CN112528660A (en) * | 2020-12-04 | 2021-03-19 | 北京百度网讯科技有限公司 | Method, apparatus, device, storage medium and program product for processing text |
| WO2021139424A1 (en) * | 2020-05-14 | 2021-07-15 | 平安科技（深圳）有限公司 | Text content quality evaluation method, apparatus and device, and storage medium |
| CN113255583A (en) * | 2021-06-21 | 2021-08-13 | 中国平安人寿保险股份有限公司 | Data annotation method and device, computer equipment and storage medium |
-
2021
- 2021-08-24 CN CN202110974826.8A patent/CN113657325B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2004057458A2 (en) * | 2002-12-17 | 2004-07-08 | Terastat, Inc. | Method and system for dynamic visualization of multi-dimensional data |
| US20100306242A1 (en) * | 2009-05-30 | 2010-12-02 | Edmond Kwok-Keung Chow | Methods and Systems for Annotation of Digital Informatin |
| CN103970859A (en) * | 2014-04-29 | 2014-08-06 | 杨立法 | Google user map text labeling method based on SVG |
| CN110162779A (en) * | 2019-04-04 | 2019-08-23 | 北京百度网讯科技有限公司 | Appraisal procedure, device and the equipment of quality of case history |
| CN110968708A (en) * | 2019-12-20 | 2020-04-07 | 华中师范大学 | Method and system for labeling education information resource attributes |
| CN111460765A (en) * | 2020-03-30 | 2020-07-28 | 掌阅科技股份有限公司 | Electronic book labeling processing method, electronic equipment and storage medium |
| WO2021139424A1 (en) * | 2020-05-14 | 2021-07-15 | 平安科技（深圳）有限公司 | Text content quality evaluation method, apparatus and device, and storage medium |
| CN111767410A (en) * | 2020-06-30 | 2020-10-13 | 平安国际智慧城市科技股份有限公司 | Construction method, device, equipment and storage medium of clinical medical knowledge map |
| CN111814664A (en) * | 2020-07-07 | 2020-10-23 | 广联达科技股份有限公司 | Method and device for identifying marks in drawing, computer equipment and storage medium |
| CN111816311A (en) * | 2020-07-22 | 2020-10-23 | 北京捷通华声科技股份有限公司 | State identification method, system and device |
| CN112507090A (en) * | 2020-11-30 | 2021-03-16 | 北京百度网讯科技有限公司 | Method, apparatus, device and storage medium for outputting information |
| CN112528660A (en) * | 2020-12-04 | 2021-03-19 | 北京百度网讯科技有限公司 | Method, apparatus, device, storage medium and program product for processing text |
| CN113255583A (en) * | 2021-06-21 | 2021-08-13 | 中国平安人寿保险股份有限公司 | Data annotation method and device, computer equipment and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 耿骞等: "融合词语义表示和新词发现的领域本体演化——以产品评论数据为例", 《图书情报工作.》, 30 April 2021 (2021-04-30) * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116522935A (en) * | 2023-03-29 | 2023-08-01 | 北京德风新征程科技股份有限公司 | Text data processing method, processing device and electronic equipment |
| CN116522935B (en) * | 2023-03-29 | 2024-03-29 | 北京德风新征程科技股份有限公司 | Text data processing method, processing device and electronic equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113657325B (en) | 2024-04-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10628476B2 (en) | Information processing apparatus, information processing method, information processing system, and storage medium | |
| US11488693B2 (en) | Abstracting information from patient medical records | |
| US11709877B2 (en) | Systems and methods for targeted annotation of data | |
| US11714791B2 (en) | Automated generation of revision summaries | |
| US20230154593A1 (en) | Systems and methods for medical data processing | |
| US20190171714A1 (en) | Artificial Intelligence Quality Measures Data Extractor | |
| CN112562808A (en) | Patient portrait generation method and device, electronic equipment and storage medium | |
| Zhegallo et al. | ETRAN—R extension package for eye tracking results analysis | |
| US20190122750A1 (en) | Auto-populating patient reports | |
| CN116992839B (en) | Automatic generation method, device and equipment for medical records front page | |
| US20230060235A1 (en) | Multi-stage workflow processing and analysis platform | |
| CN113657325B (en) | Method, apparatus, medium and program product for determining annotation style information | |
| CN110471941A (en) | It is automatically positioned the method, apparatus and electronic equipment of judgment basis | |
| CN112784588A (en) | Method, device, equipment and storage medium for marking text | |
| CN115620886B (en) | Data auditing method and device | |
| Gandhi et al. | A narrative review with a step-by-step guide to R software for clinicians: Navigating medical data analysis in cancer research | |
| CN113345542B (en) | Electronic medical record management method, device, equipment, storage medium and computer program product | |
| CN106537372A (en) | Entity recognition for enhanced document productivity | |
| CN112925876B (en) | Method, device, medium and equipment for processing structured medical record migrated across sites | |
| CN112786132B (en) | Medical record text data segmentation method and device, readable storage medium and electronic equipment | |
| JP7519260B2 (en) | Training data generation system and training data generation method | |
| US20230395209A1 (en) | Development and use of feature maps from clinical data using inference and machine learning approaches | |
| US11574701B1 (en) | Computing system for normalizing computer-readable genetic test results from numerous different sources | |
| Blakeney et al. | Development and Usability Testing of a System to Detect Adverse Events and Medical Mistakes | |
| Yu et al. | AIPatient: Simulating Patients with EHRs and LLM Powered Agentic Workflow |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |