CN112259183A - Method and device for extracting patient health time axis based on electronic medical record - Google Patents
Method and device for extracting patient health time axis based on electronic medical record Download PDFInfo
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Abstract
The invention provides a method and a device for extracting a patient health time axis based on an electronic medical record, and the scheme comprises the following steps: acquiring an electronic medical record of a target patient; preprocessing the electronic medical record; extracting a target field from the preprocessed electronic medical record; establishing a patient health time axis based on the target field, and recording the patient health time axis as a candidate health time axis; acquiring a historical medical record of the target patient; judging whether entities corresponding to the entities in the candidate health time axis and the entity time exist in the historical medical records, and if so, replacing the entity names in the candidate patient health time axis with the entity names in the historical medical records; and outputting the candidate patient health time axis after the entity name is replaced as a target health time axis, so that the health time axis of the patient is quickly generated.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a method and a device for extracting a patient health time axis based on an electronic medical record.
Background
Medical personnel need to comprehensively know the health condition of a patient in the process of diagnosing, diagnosing and nursing the patient, and important diagnosis and treatment information is quickly screened out from the health condition through clinical thinking and logical reasoning. However, in reality, patient information is not comprehensive, a large amount of data is not standardized, the information is not emphasized, and even clinical judgment of medical staff is interfered. If the technology is available, medical staff can comprehensively know the medical history of the patient and the whole diagnosis and treatment process, the important information of the patient can be visually checked in a long line, and clinical basis is provided for the medical process.
Therefore, there is an urgent need for a solution that can quickly generate a patient health timeline.
Disclosure of Invention
In view of this, the embodiment of the present invention provides an extraction method of a patient health timeline based on an electronic medical record, so as to realize rapid generation of the patient health timeline.
In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:
a method for extracting a patient health timeline based on an electronic medical record comprises the following steps:
acquiring an electronic medical record of a target patient;
preprocessing the electronic medical record;
extracting a target field from the preprocessed electronic medical record;
carrying out normalized processing on the entity and the entity time in the target field;
establishing a patient health time axis based on the target field, and recording the patient health time axis as a candidate health time axis;
acquiring a historical medical record of the target patient;
judging whether entities corresponding to the entities in the candidate health time axis and the entity time exist in the historical medical records, and if so, replacing the entity names in the candidate patient health time axis with the entity names in the historical medical records;
and outputting the candidate patient health time axis after the entity name is replaced as a target health time axis.
Optionally, in the method for extracting a health timeline of a patient based on an electronic medical record, the electronic medical record is preprocessed, which includes:
carrying out structuralization processing on the electronic medical record to obtain an entity name;
and carrying out data cleaning on the structured data.
Optionally, in the method for extracting a patient health timeline based on an electronic medical record, the target fields include, but are not limited to:
a combination of one or more of a symptom field, an exam field, a test field, a disease field, a surgery field, a radiation therapy field, and a chemotherapy field.
Optionally, in the method for extracting a patient health timeline based on an electronic medical record, acquiring the electronic medical record of the target patient includes:
acquiring an in-patient medical record document and an out-patient medical record document of a target patient;
the medical record document for hospitalization comprises: admission record, examination report, pathological report, examination report, operation record, and medical advice; the outpatient medical record document comprises: clinic case history, clinic medical advice, clinic examination report, and clinic examination report.
Optionally, in the method for extracting a patient health timeline based on an electronic medical record, before determining whether an entity in the candidate health timeline and an entity corresponding to the entity time exist in the historical medical record, the method further includes:
and judging whether a first target field and a second target field with the same entity time exist in the candidate health time axis, if so, judging whether the entities in the first target field and the second target field are the same, if so, removing the redundant first target field or the redundant second target field, and if not, adding the entity of the first target field and the related content of the entity into the second target field.
An extraction device of a patient health time axis based on an electronic medical record comprises:
the data acquisition unit is used for acquiring the electronic medical record of the target patient;
the data processing unit is used for preprocessing the electronic medical record, extracting a target field from the preprocessed electronic medical record and carrying out normalized processing on an entity in the target field and entity time;
the candidate health time axis establishing unit is used for establishing a patient health time axis based on the target field and recording the patient health time axis as a candidate health time axis;
and the candidate health time axis optimization unit is used for acquiring the historical medical record of the target patient, judging whether entities corresponding to the entities in the candidate health time axis and the entity time exist in the historical medical record, if so, replacing the entity names in the candidate health time axis of the patient by the entity names in the historical medical record, and outputting the candidate health time axis of the patient with the replaced entity names as the target health time axis.
Optionally, in the above apparatus for extracting a health timeline of a patient based on an electronic medical record, when the data processing unit preprocesses the electronic medical record, the data processing unit is specifically configured to:
carrying out structuralization processing on the electronic medical record to obtain an entity name;
and carrying out data cleaning on the structured data.
Optionally, in the above apparatus for extracting a patient health timeline based on an electronic medical record, the data processing unit extracts a target field from the preprocessed electronic medical record, and is specifically configured to:
extracting a combination of one or more of a symptom field, an examination field, a test field, a disease field, a surgery field, a radiotherapy field, and a chemotherapy field from the pre-processed electronic medical record.
Optionally, in the above apparatus for extracting a patient health timeline based on an electronic medical record, the data acquisition unit acquires an electronic medical record duration of a target patient, and is specifically configured to:
acquiring an in-patient medical record document and an out-patient medical record document of a target patient from a medical record database;
the medical record document for hospitalization comprises: admission record, examination report, pathological report, examination report, operation record, and medical advice; the outpatient medical record document comprises: clinic case history, clinic medical advice, clinic examination report, and clinic examination report.
Optionally, in the above apparatus for extracting a patient health timeline based on an electronic medical record, before determining whether an entity in the candidate health timeline and an entity corresponding to the entity time exist in the historical medical record, the apparatus further includes:
and judging whether a first target field and a second target field with the same entity time exist in the candidate health time axis, if so, judging whether the entities in the first target field and the second target field are the same, if so, removing the redundant first target field or the redundant second target field, and if not, adding the entity of the first target field and the related content of the entity into the second target field.
Based on the technical scheme, the scheme provided by the embodiment of the invention obtains the electronic medical record of the target patient; preprocessing the electronic medical record; extracting a target field from the preprocessed electronic medical record; establishing a patient health time axis based on the target field, and recording the patient health time axis as a candidate health time axis; acquiring a historical medical record of the target patient; judging whether entities corresponding to the entities in the candidate health time axis and the entity time exist in the historical medical records, and if so, replacing the entity names in the candidate patient health time axis with the entity names in the historical medical records; and outputting the candidate patient health time axis after the entity name is replaced as a target health time axis, so that the health time axis of the patient is quickly generated.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for extracting a patient health timeline based on an electronic medical record disclosed in an embodiment of the present application;
FIG. 2 is a schematic flow chart of a method for extracting a patient health timeline based on electronic medical records according to another embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an embodiment of a device for extracting a patient health timeline based on an electronic medical record.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The application provides a method and a device for extracting a health time axis of a patient, wherein the health time axis can be quickly extracted according to an electronic medical record.
Referring to fig. 1, an embodiment of the present application provides a method for extracting a patient health timeline based on an electronic medical record, including:
step S101: acquiring an electronic medical record of a target patient;
electronic Medical Records (EMRs) are also called computerized medical record systems or computer-based patient records. It is a digitalized medical record stored, managed, transmitted and reproduced by electronic equipment (computer, health card, etc.) to replace the hand-written paper case history. Its contents include all the information of the paper case history. Electronic medical record systems provide users with the ability to access complete and accurate data, alerts, reminders, and clinical decision support systems.
In this scenario, the electronic medical record of the patient refers to a medical record document stored in an electronic version form, which may include an in-patient medical record document and an out-patient medical record document, and the in-patient medical record document includes: admission record, examination report, pathological report, examination report, operation record, and medical advice; the outpatient medical record document comprises: clinic case history, clinic medical advice, clinic examination report, and clinic examination report.
During the process of acquiring the electronic disease of the target patient, the electronic disease can be acquired by a local database of a hospital or a cloud database, and the cloud database can be associated with a medical record database of any registered medical institution;
step S102: preprocessing the electronic medical record;
in the scheme, the preprocessing can refer to performing structural processing on the electronic medical record to obtain an entity name; and carrying out data cleaning on the structured data.
The preprocessing action can be realized through a medical record model, and after the electronic medical record of the target patient is acquired, the electronic medical record can be preprocessed through the medical record model. The medical record model is based on electronic record data, the electronic record data is stored according to a defined structure according to a structured data structure defined by an applicable scene, and the structure of the electronic record after the structure storage can be shown in table 1.
TABLE 1
For example, the electronic medical record data of the target patient is: ' when the patient walks quickly more than 2 years before admission, the patient feels pressure-like pain at the back of the sternum, can endure the pain, radiates to the two upper limbs and the shoulder and back, and relieves the pain by self after having a rest for about 10 minutes without palpitation, dyspnea, cold sweat, hyperhidrosis and dizziness, , syncope, epigastric discomfort, nausea, vomiting and the like, wherein the symptoms of the later complaint are interrupted to attack during activity, the degree gradually worsens in nearly 1 month, about 1-3 times a day, the duration is prolonged, the maximum time reaches 20 minutes, unstable angina is diagnosed in a Zhen hospital, coronary angiography examination shows LM (-), long and narrow lesion at the far end in LAD, the maximum weight of stenosis is 70-80%, long and narrow lesion at the far end of LCX, the maximum weight of stenosis is 80%, branch reduction after RCA is irregular, the opening is 80% narrow, one stent is implanted at the far end of LCX, the secondary prevention and treatment of postoperative regular coronary heart disease is realized, chest pain does not recur, and the vitamin is not used after 1 year. The patient suffered from the pain after the activity before 7 months suffered from the squeeze of the rear part of the sternum, the property, the duration and the relieving mode are the same as those before, the chest pain repeatedly attacks during the activity for nearly 1 month, the pain lasts for 5-20 minutes for 1-3 times a day, and the pain can be relieved by taking the nitroglycerin. For further diagnosis and treatment, unstable angina pectoris was admitted to the hospital. The patient has good spirit, good sleep, good appetite, no abnormality in urination, normal urine volume, no abnormality in defecation and no obvious change in weight since the patient suffers from a disease. ".
The medical record data after the medical record model is adopted to carry out the structuralized processing on the medical record data is changed into:
the medical record data after the structured processing can be displayed in a list form;
when the electronic medical record is preprocessed, the electronic medical record can be cleaned besides the electronic medical record is subjected to structural processing; the cleaning refers to cleaning redundant data in the electronic medical record, and of course, the medical record model may also be used to perform normalization processing on entities and time nodes in the electronic medical record, where the normalization processing refers to: based on the medical entity synonym library and the medical record model, the structured medical record data is cleaned and standardized, and the following table 2 is the medical record data before and after cleaning and standardization of a certain patient:
different entity names used for representing the same meaning in the medical record data after the structuring processing are summarized and unified into the same entity name, wherein the entity refers to a medical entity and a medical entity: for the purpose of observing and distinguishing things in medicine, the commonly used medical entities include symptoms, diseases, examinations, operations, medicines, etc.
For example, referring to Table 2, in Table 2, the before-cleaning and standardizing column is used to characterize the name expressions of the medical entities before cleaning and standardizing, the after-cleaning and standardizing column is used to characterize the name expressions of the medical entities after cleaning and standardizing,
TABLE 2
| Before cleaning and standardizing | After cleaning and standardization |
| Hypertension (hypertension) | Hypertension (hypertension) |
| Hypertension disease | Hypertension (hypertension) |
| Is hypertension? | Hypertension (hypertension) |
| Coronary atherosclerotic heart disease | Coronary arteryAtherosclerotic heart disease |
| Coronary heart disease | Coronary atherosclerotic heart disease |
| Coronary atherosclerotic heart disease | Coronary atherosclerotic heart disease |
| Coronary heart disease? | Coronary atherosclerotic heart disease |
In addition to cleaning and standardizing the medical entities in the structured medical record data, the time nodes in the structured medical record data can be cleaned and standardized, and during processing, the time nodes are normalized by using a regular expression, and different time expression modes are subjected to unified identification, as shown in table 2 below, the original time nodes in table 2 are expression modes of the time nodes before the normalization, and the normalized time is an expression mode of the time nodes after the normalization.
TABLE 2
Step S103: extracting a target field from the preprocessed electronic medical record;
in this scheme, the target field may include seven major classes: the electronic medical record comprises a symptom field, an examination field, a check field, a disease field, an operation field, a radiotherapy field and a chemotherapy field, wherein each field in the electronic medical record can be judged by adopting a medical classified word bank, and whether the fields belong to the symptom field, the examination field, the check field, the disease field, the operation field, the radiotherapy field or the chemotherapy field is judged; during design, one or more fields in the fields can be selected as target fields in the application according to requirements, and the health condition of the user can be represented through the target fields;
step S104: establishing a patient health time axis based on the target field, and recording the patient health time axis as a candidate health time axis;
after the target point is determined, the medical entity in the target field and the entity time corresponding to the medical entity are extracted, so that a health time axis of the target patient can be established, and the historical change condition of the physical health condition of the target patient can be displayed through the health time axis.
Step S105: acquiring a historical medical record of the target patient;
in this step, considering that the representation form of the medical entity after the normalization processing may not be more intuitive than the representation form of the medical entity in the historical medical record, the medical entity after the normalization processing in the candidate health time axis of the medical entity in the historical medical record may be adopted; the processing mode preferentially reserves objective medical records for treatment, not only reserves complete patient information, but also ensures the accuracy of the patient information, and provides effective basis for clinical judgment.
Based on the above purposes, in this step, after the candidate health timeline is obtained, a historical medical record of the target patient needs to be obtained;
step S106: judging whether entities corresponding to the entities in the candidate health time axis and the entity time exist in the historical medical records or not, and if so, executing a step S107;
in this step, based on the entities in the candidate health time axis and the entity time corresponding to the entities, determining the entities with the same representation object as the entities in the candidate health time axis and the entity time corresponding to the entities in the historical medical record, judging whether the description form of the entities in the candidate health time axis is the same as the description form of the entities in the historical medical record, if so, continuing to traverse other entities in the candidate health time axis and the entity time, and if not, executing step S107; in this step, if the objects represented by the two entities are consistent, it indicates that the two entities are corresponding, and in this scheme, whether the two entities represent the objects consistently can be determined by a preset medical entity word stock, for example, with respect to the entity name: coronary heart disease, coronary atherosclerotic heart disease, these three entity names, although the expression form is different, but all three correspond to same medical entity, namely: coronary atherosclerotic heart disease, therefore, the three can be used as the similar meaning words, whether the entities corresponding to the entities in the candidate health time axis and the entity time exist in the historical medical record can be inquired through a similar meaning word bank, and the entities in the historical medical record and the description thereof are more objective, so that the entity names in the historical medical record are adopted to replace the corresponding entity names in the candidate health time axis, and certainly, the symptom description corresponding to the entities in the historical medical record can be added to the fields corresponding to the entities in the candidate health time axis.
Step S107: replacing the entity names in the candidate patient health timeline with the entity names in the historical medical records;
step S108: and outputting the candidate patient health time axis after the entity name is replaced as a target health time axis.
Further, in the technical solution disclosed in the embodiment of the present application, referring to fig. 2, in order to simplify the target health timeline, after the candidate health timeline is obtained, the following operations may be performed:
step S201: judging whether a first target field and a second target field with the same entity time exist in the candidate health time axis, if so, executing a step S202;
in this step, if some fields in the candidate health timeline have the same entity time, these fields are considered to have redundant data;
step S202: judging whether the entities in the first target field and the second target field are the same or not, if so, executing a step S203, and if not, executing a step S204;
if the entities in the first target field and the second target field are the same, it indicates that the two fields express the same event, and therefore, step S203 needs to be executed to remove one of the fields;
step S203: removing redundant first target fields or second target fields;
step S204: appending the entity and entity-related content of the first target field to the second target field;
if the entity time of the first target field is the same as that of the second target field, and the entity time of the first target field is different from that of the second target field, the entity time of the first target field is considered to have redundant data, so that the two fields can be combined into one field, the combined fields share one entity time, the entity and the entity related content of the first target field are added to the second target field, and the entity related content of the second target field can be added to the first target field.
In this embodiment, corresponding to the method for extracting the patient health timeline based on the electronic medical record, the present application also discloses an apparatus for extracting the patient health timeline based on the electronic medical record, and the detailed working contents of each unit please refer to the contents of the above method embodiments.
The following describes an extraction apparatus based on an electronic medical record health timeline according to an embodiment of the present invention, and the extraction apparatus based on the electronic medical record health timeline described below and the extraction method based on the electronic medical record health timeline described above can be referred to correspondingly.
Referring to fig. 3, an apparatus for extracting a patient health timeline based on an electronic medical record provided in an embodiment of the present application includes:
a data acquisition unit 100, corresponding to step S101 in the method, for acquiring an electronic medical record of a target patient;
a data processing unit 200, corresponding to steps S102 and S103 in the above method, for preprocessing the electronic medical record and extracting a target field from the preprocessed electronic medical record;
a candidate health timeline establishing unit 300, corresponding to step S104 in the above method, for establishing a patient health timeline based on the target field, and recording as a candidate health timeline;
and a candidate health timeline optimizing unit 400, corresponding to steps S105 to S108 in the method, configured to obtain a historical medical record of the target patient, determine whether an entity corresponding to the entity in the candidate health timeline and the entity time exists in the historical medical record, if so, replace the entity name in the candidate health timeline with the entity name in the historical medical record, and output the candidate health timeline with the entity name replaced as the target health timeline.
Corresponding to the above method embodiment, when the data processing unit preprocesses the electronic medical record, the data processing unit is specifically configured to:
carrying out structuralization processing on the electronic medical record to obtain an entity name;
carrying out data cleaning on the structured data;
and carrying out normalized processing on the entities and the entity time in the target field.
Corresponding to the above method embodiment, the data processing unit extracts the target field from the preprocessed electronic medical record, and is specifically configured to:
extracting a combination of one or more of a symptom field, an examination field, a test field, a disease field, a surgery field, a radiotherapy field, and a chemotherapy field from the pre-processed electronic medical record.
Corresponding to the above method embodiment, the data acquisition unit acquires the electronic duration of the target patient, and is specifically configured to:
acquiring an in-patient medical record document and an out-patient medical record document of a target patient from a medical record database;
the medical record document for hospitalization comprises: admission record, examination report, pathological report, examination report, operation record, and medical advice; the outpatient medical record document comprises: clinic case history, clinic medical advice, clinic examination report, and clinic examination report.
Corresponding to the above method embodiment, determining whether there is an entity in the historical medical records corresponding to the entity in the candidate health timeline and the entity time, further includes:
and judging whether a first target field and a second target field with the same entity time exist in the candidate health time axis, if so, judging whether the entities in the first target field and the second target field are the same, if so, removing the redundant first target field or the redundant second target field, and if not, adding the entity of the first target field and the related content of the entity into the second target field.
For convenience of description, the above system is described with the functions divided into various modules, which are described separately. Of course, the functionality of the various modules may be implemented in the same one or more software and/or hardware implementations of the invention.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the system or system embodiments are substantially similar to the method embodiments and therefore are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for related points. The above-described system and system embodiments are only illustrative, wherein the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
It is further noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for extracting a patient health time axis based on an electronic medical record is characterized by comprising the following steps:
acquiring an electronic medical record of a target patient;
preprocessing the electronic medical record;
extracting a target field from the preprocessed electronic medical record;
establishing a patient health time axis based on the target field, and recording the patient health time axis as a candidate health time axis;
acquiring a historical medical record of the target patient;
judging whether entities corresponding to the entities in the candidate health time axis and the entity time exist in the historical medical records, and if so, replacing the entity names in the candidate patient health time axis with the entity names in the historical medical records;
and outputting the candidate patient health time axis after the entity name is replaced as a target health time axis.
2. The method for extracting the patient health timeline based on the electronic medical record as claimed in claim 1, wherein the preprocessing the electronic medical record comprises:
carrying out structuralization processing on the electronic medical record to obtain an entity name;
cleaning the non-standard data in the electronic medical record;
and carrying out normalized processing on the entities and the entity time in the target field.
3. The method for extracting the patient health timeline based on the electronic medical record as claimed in claim 1, wherein the target fields include but are not limited to:
a combination of one or more of a symptom field, an exam field, a test field, a disease field, a surgery field, a radiation therapy field, and a chemotherapy field.
4. The method for extracting the patient health timeline based on electronic medical records according to claim 1, wherein the obtaining of the electronic medical record of the target patient comprises:
acquiring an in-patient medical record document and an out-patient medical record document of a target patient;
the medical record document for hospitalization comprises: admission record, examination report, pathological report, examination report, operation record, and medical advice; the outpatient medical record document comprises: clinic case history, clinic medical advice, clinic examination report, and clinic examination report.
5. The method of claim 1, wherein determining whether there are entities in the historical medical records that correspond to the entities in the candidate health timeline and the entity time further comprises:
and judging whether a first target field and a second target field with the same entity time exist in the candidate health time axis, if so, judging whether the entities in the first target field and the second target field are the same, if so, removing the redundant first target field or the redundant second target field, and if not, adding the entity of the first target field and the related content of the entity into the second target field.
6. An extraction device of a patient health time axis based on an electronic medical record is characterized by comprising:
the data acquisition unit is used for acquiring the electronic medical record of the target patient;
the data processing unit is used for preprocessing the electronic medical record and extracting a target field from the preprocessed electronic medical record;
the candidate health time axis establishing unit is used for establishing a patient health time axis based on the target field and recording the patient health time axis as a candidate health time axis;
and the candidate health time axis optimization unit is used for acquiring the historical medical record of the target patient, judging whether entities corresponding to the entities in the candidate health time axis and the entity time exist in the historical medical record, if so, replacing the entity names in the candidate health time axis of the patient by the entity names in the historical medical record, and outputting the candidate health time axis of the patient with the replaced entity names as the target health time axis.
7. The device for extracting a patient health timeline based on an electronic medical record as claimed in claim 6, wherein the data processing unit is specifically configured to, when preprocessing the electronic medical record:
carrying out structuralization processing on the electronic medical record to obtain an entity name;
carrying out data cleaning on the structured data;
and carrying out normalized processing on the entities and the entity time in the target field.
8. The device for extracting a patient health timeline based on electronic medical records of claim 6, wherein the data processing unit extracts a target field from the preprocessed electronic medical record, and is specifically configured to:
extracting a combination of one or more of a symptom field, an examination field, a test field, a disease field, a surgery field, a radiotherapy field, and a chemotherapy field from the pre-processed electronic medical record.
9. The device for extracting a patient health timeline based on electronic medical records of claim 6, wherein the data acquisition unit acquires the electronic medical duration of the target patient, and is specifically configured to:
acquiring an in-patient medical record document and an out-patient medical record document of a target patient from a medical record database;
the medical record document for hospitalization comprises: admission record, examination report, pathological report, examination report, operation record, and medical advice; the outpatient medical record document comprises: clinic case history, clinic medical advice, clinic examination report, and clinic examination report.
10. The apparatus as claimed in claim 6, wherein the determining whether there is an entity in the historical medical records that corresponds to the entity in the candidate health timeline and the entity time before, further comprises:
and judging whether a first target field and a second target field with the same entity time exist in the candidate health time axis, if so, judging whether the entities in the first target field and the second target field are the same, if so, removing the redundant first target field or the redundant second target field, and if not, adding the entity of the first target field and the related content of the entity into the second target field.
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