KR101744800B1 - System for providing medical information - Google Patents
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- KR101744800B1 KR101744800B1 KR1020150053326A KR20150053326A KR101744800B1 KR 101744800 B1 KR101744800 B1 KR 101744800B1 KR 1020150053326 A KR1020150053326 A KR 1020150053326A KR 20150053326 A KR20150053326 A KR 20150053326A KR 101744800 B1 KR101744800 B1 KR 101744800B1
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- 201000010099 disease Diseases 0.000 claims abstract description 20
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims abstract description 20
- 238000004458 analytical method Methods 0.000 claims abstract description 18
- 238000000034 method Methods 0.000 claims abstract description 10
- 208000031940 Disease Attributes Diseases 0.000 claims description 8
- 238000001914 filtration Methods 0.000 claims description 8
- 230000003466 anti-cipated effect Effects 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 18
- 230000000052 comparative effect Effects 0.000 description 10
- 238000000605 extraction Methods 0.000 description 4
- 238000010606 normalization Methods 0.000 description 4
- 238000003745 diagnosis Methods 0.000 description 3
- 239000011159 matrix material Substances 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 239000000284 extract Substances 0.000 description 2
- 230000014509 gene expression Effects 0.000 description 2
- 238000003491 array Methods 0.000 description 1
- 230000000721 bacterilogical effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000035622 drinking Effects 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 210000003608 fece Anatomy 0.000 description 1
- 230000002489 hematologic effect Effects 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 230000029058 respiratory gaseous exchange Effects 0.000 description 1
- 230000000405 serological effect Effects 0.000 description 1
- 230000036578 sleeping time Effects 0.000 description 1
- 230000000391 smoking effect Effects 0.000 description 1
- 210000002700 urine Anatomy 0.000 description 1
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- G06F19/3431—
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/22—Social work or social welfare, e.g. community support activities or counselling services
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Abstract
A medical information providing system is disclosed. Wherein the medical information providing system comprises: an input unit for receiving attribute information of a patient; A case extracting unit for applying a hierarchical analysis method (AHP: Analytic Hierarchy Process) to the input attribute information to assign a weight for each attribute, and comparing the attribute information of the patient with the weighted patient case information and the stored patient case information to extract a similar case; And a case analysis unit for analyzing the similar cases and providing anticipated disease information and optimal examination information for the patient.
Description
BACKGROUND OF THE
The Clinical Decision Support System is a system that allows the physician to provide the necessary foundation knowledge to determine and judge the diagnosis or treatment policy in the patient's care, . In addition to the subjective judgment of the physician in the examination of the patient by the doctor, the medical guideline is implemented by the computer and the result of the guideline of the patient's condition is informed to the physician to prevent misdiagnosis and enable more objective medical treatment do.
In this regard, Patent Registration No. 10-1066246 relates to a system and method for supporting a clinical decision support system, which is a system that is independent of a hospital information system, and which combines a knowledge- We are building a support system.
SUMMARY OF THE INVENTION The present invention provides a medical information providing system for extracting a case similar to a patient and providing information for supporting clinical decision making.
It is another object of the present invention to provide a medical information providing system capable of providing highly reliable information with an emphasis on an attribute item which is judged to be important by reflecting a weight on various attribute information of a patient.
It is another object of the present invention to provide a medical information providing system capable of providing customized information by giving high weight to a preferred medical care provider.
The present invention also provides a medical information providing system that can provide information that can be intuitively judged by numerically providing an expected prediction value of a disease and a recommended test value.
According to an aspect of the present invention, there is provided an information processing apparatus including an input unit for inputting attribute information of a patient; A case extracting unit for applying a hierarchical analysis method (AHP: Analytic Hierarchy Process) to the input attribute information to assign a weight for each attribute, and comparing the attribute information of the patient with the weighted patient case information and the stored patient case information to extract a similar case; And a case analysis unit for analyzing the similar cases and providing anticipated disease information and optimal test information for the patient.
The attribute information of the patient may be configured to include a human attribute, a clinical attribute, a test attribute, and a disease attribute.
The case extracting unit may include an attribute distance calculating unit for calculating a distance between the attribute information of the patient and the previously stored patient case information; A weight applying unit for assigning a weight for each attribute to the calculated distance between the attributes; A summation unit for summing the distance values of the weighted attributes; And a filtering unit for filtering the sum value by comparing the sum value with a reference value.
Wherein the weight applying unit comprises: a comparing unit for giving preference to the input attribute information through a pair comparison; A standardization unit for performing standardization on preference per property; And a calculation unit for calculating a weight for each attribute using the standard value calculated by the standardization unit.
The comparison unit may perform the pair comparison using the weight of each existing property stored in the storage unit.
The comparing unit may perform the twin comparison using the average value of the existing weight values given by the selected medical staff among the data stored in the storing unit.
The comparison unit may perform the pair comparison using the average value of the existing weight values given by the medical staff having a career or more of the data stored in the database.
The comparison unit may perform the pair comparison using the average value of the existing weight values given by the medical staff performing the tasks related to the disease information shown in the attribute information of the patient among the data stored in the database.
The comparison unit may perform the twin comparison using the average value of the existing weight values given by the medical staff engaged in the selected medical care out of the data stored in the database.
The case analyzer may provide a probability of occurrence of the anticipated disease information according to the sum value.
The case analyzer may provide a recommendation value of the optimal test information with reference to the progress of the similar case with respect to the optimal test information to be provided.
The medical information providing system of the present invention can provide information for supporting clinical decision making by extracting a case similar to a patient.
In addition, reliable information can be provided with an emphasis on the attribute items which are judged to be important by reflecting the weight on the various attribute information of the patient.
In addition, it is possible to give a high weight to a preferred medical care provider, thereby providing customized information.
In addition, it is possible to provide information that can be intuitively judged by providing numerical predictions of expected disease outbreak predictions and recommendation values of recommended tests.
1 is a block diagram of a medical information providing system according to an embodiment of the present invention;
2 is a block diagram of a case extracting unit according to an embodiment of the present invention;
3 is a block diagram of a weight applying unit according to an embodiment of the present invention.
FIG. 4 is a conceptual diagram of attribute information of a patient according to an embodiment of the present invention;
FIG. 5 is a conceptual diagram of patient case information according to an embodiment of the present invention;
FIG. 6 is a conceptual diagram of distances according to an embodiment of the present invention,
FIG. 7 is a conceptual diagram of a similar case extraction process according to an embodiment of the present invention; FIG.
8 is an analysis conceptual diagram of a case analysis unit according to an embodiment of the present invention;
9 is an analysis conceptual diagram of a case analysis unit according to another embodiment of the present invention.
The present invention is capable of various modifications and various embodiments, and specific embodiments are illustrated and described in the drawings. It should be understood, however, that the invention is not intended to be limited to the particular embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
The terms including ordinal, such as second, first, etc., may be used to describe various elements, but the elements are not limited to these terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the second component may be referred to as a first component, and similarly, the first component may also be referred to as a second component. And / or < / RTI > includes any combination of a plurality of related listed items or any of a plurality of related listed items.
It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, . On the other hand, when an element is referred to as being "directly connected" or "directly connected" to another element, it should be understood that there are no other elements in between.
The terminology used in this application is used only to describe a specific embodiment and is not intended to limit the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the terms "comprises" or "having" and the like are used to specify that there is a feature, a number, a step, an operation, an element, a component or a combination thereof described in the specification, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.
Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Do not.
Hereinafter, embodiments will be described in detail with reference to the accompanying drawings, wherein like or corresponding elements are denoted by the same reference numerals, and redundant description thereof will be omitted.
1 is a block diagram of a medical information providing system according to an embodiment of the present invention.
Referring to FIG. 1, a medical
The
The
When the patient's attribute information is input, the
FIG. 2 is a block diagram of a case extracting unit according to an embodiment of the present invention.
2, the
The
The
3 is a block diagram of a weight applying unit according to an embodiment of the present invention.
Referring to FIG. 3, the
The comparing
The
Or the comparing
Or the comparing
Alternatively, the comparing
Alternatively, the
Alternatively, the
The
The calculating
The comparing
[Equation 1]
Attributes for calculating weights include human attributes, clinical attributes, and disease attributes, and the numbers listed in the matrix represent the preferences among the attributes. The higher the value in the matrix is, the higher the value is compared with the relative attribute, and the smaller the value, the smaller the preference.
The attribute information for determining the weight can be largely classified into human attribute, clinical attribute, inspection attribute, and disease attribute. In one embodiment of the present invention, the weight calculation process according to the classification will be described. However, it is to be understood that the attribute information is not limited to the above, and that the weights can be calculated on the basis of the detailed attributes belonging to the human attribute, the clinical attribute, the test attribute, and the disease attribute.
As described above, the comparing
Next, the
&Quot; (2) "
Next, the
&Quot; (3) "
&Quot; (4) "
Next, the calculating
&Quot; (5) "
The
The
The
The similar case extraction process of the case extracting unit described above can be performed according to the following equation (6).
&Quot; (6) "
here,
Is the property information of each patient And the attributes of the pre-stored patient case information Quot; Denotes a weight for each attribute, Means each attribute from 1 to n, Means the sum of weights for each property.therefore
The patient's attribute information And pre-stored patient case information , Which indicates the similarity between the patient's attribute information and the pre-stored patient case information.Referring again to FIG. 1, the
At this time, the
In addition, the
The
In addition, the
The
4 is a conceptual diagram of attribute information of a patient according to an embodiment of the present invention. In FIG. 4, the sex and age of the patient refers to human attributes, respiration and pulse to clinical attributes,
5 is a conceptual diagram of patient case information according to an embodiment of the present invention. In Figure 5, patient case information was set as 100 samples.
FIG. 6 is a conceptual diagram of distances according to an embodiment of the present invention. In FIG. 6, the distance between the respective attributes means a distance value before the weight is given. In the case of sex and disease, '1' is indicated for matching, and '0' is indicated for non-matching.
7 is a conceptual diagram of a similar case extraction process according to an embodiment of the present invention. In FIG. 7, the order of similarity is ranked from the lowest value to the lowest value, and caes2 and case99 are selected as similar cases according to the reference value (0.100).
8 is an analysis conceptual diagram of a case analysis unit according to an embodiment of the present invention. In FIG. 8, the case analyzer provides the estimated disease information for the patient using the selected similar case, and provides the probability of the expected disease information together with the sum of the similar case and the similar case.
9 is an analysis conceptual diagram of a case analysis unit according to another embodiment of the present invention. In FIG. 9, the case analyzer provides the optimal test information using the selected similar case, and provides the recommended value of the optimal test information with reference to the progress of the similar case.
As used in this embodiment, the term " portion " refers to a hardware component such as software or an FPGA (field-programmable gate array) or ASIC, and 'part' performs certain roles. However, 'part' is not meant to be limited to software or hardware. &Quot; to " may be configured to reside on an addressable storage medium and may be configured to play one or more processors. Thus, by way of example, 'parts' may refer to components such as software components, object-oriented software components, class components and task components, and processes, functions, , Subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, and variables. The functions provided in the components and components may be further combined with a smaller number of components and components or further components and components. In addition, the components and components may be implemented to play back one or more CPUs in a device or a secure multimedia card.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the present invention as defined by the following claims It can be understood that
100: Input unit
200: Case extraction unit
210: Property distance calculating unit
220: weight application unit
230: summing unit
240:
300: Case Analysis Department
400:
500: Update section
Claims (11)
An input unit for receiving property information of a patient;
A case extracting unit for applying a hierarchical analysis method (AHP: Analytic Hierarchy Process) to the input attribute information to assign a weight for each attribute, and comparing the attribute information of the patient with the weighted patient case information and the stored patient case information to extract a similar case; And
And analyzing the similar case to provide the estimated disease information for the patient and the optimal examination information in which the fitness for the specific test is converted into a numerical value,
Wherein the case extracting unit comprises: an attribute distance calculating unit for calculating a distance between the attribute information of the patient and the attribute of the previously stored patient case information; A weight applying unit for assigning a weight for each attribute to the calculated distance between the attributes; A summation unit for summing the distance values of the weighted attributes; And a filtering unit for filtering the sum value by comparing the sum value with a reference value,
Wherein the weight applying unit comprises: a comparing unit for giving preference to the input attribute information through a pair comparison; A standardization unit for standardizing the preferences of each attribute according to Equation (1); And a calculation unit for calculating a weight for each attribute using the standard value calculated by the standardization unit according to the following equation (2).
[Equation 1]
&Quot; (2) "
(A1, ..., an, z1, ..., zn in Equation (1) means the inter-attribute preference, and Wa ... Wz in Equation (2)
Wherein the attribute information of the patient includes a human attribute, a clinical attribute, a test attribute, and a disease attribute.
And performing pair comparison using weight values of existing attributes stored in the storage unit.
And performs a pair comparison using an average value of existing weight values given by a selected medical caregiver among the data stored in the storage unit.
And performing a pair comparison using an average value of existing weight values given by a medical staff having a career or more of the data stored in the database.
And performing a pair comparison using an average value of existing weight values given by a medical staff performing a task related to disease information shown in the attribute information of the patient among the data stored in the database.
And performs a pair comparison using an average value of existing weight values given by a medical staff engaged in a selected medical care department among data stored in the database.
And the case analyzer provides probability of occurrence of the predicted disease information according to the sum value.
Wherein the case analyzer provides a recommendation value of the optimal test information with reference to progress of the similar case with respect to the optimal test information to be provided.
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US12073943B2 (en) | 2019-12-31 | 2024-08-27 | Coreline Soft Co., Ltd. | Medical image analysis system and similar case retrieval system using quantitative parameters, and methods for the same |
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KR101962105B1 (en) * | 2017-10-13 | 2019-03-26 | 주식회사 유비케어 | Device and method for recording medical charts |
CN111489061A (en) * | 2020-03-23 | 2020-08-04 | 天津大学 | Interactive control method for improving safety of automobile product based on virtual reality |
KR102567388B1 (en) * | 2022-05-04 | 2023-08-17 | 주식회사 타이로스코프 | A method of prescribing aid providing test set by using interview content |
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JP2002063278A (en) * | 2000-08-22 | 2002-02-28 | Shotaro Katsuki | Health degree evaluation system, its recording medium and health degree evaluating method |
KR100794516B1 (en) * | 2007-12-03 | 2008-01-14 | 한국정보통신대학교 산학협력단 | System and method for diagnosis and clinical test selection using case based machine learning inference |
JP2014233611A (en) * | 2013-06-05 | 2014-12-15 | 株式会社東芝 | Treatment planning support apparatus and treatment planning support system |
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JP2002063278A (en) * | 2000-08-22 | 2002-02-28 | Shotaro Katsuki | Health degree evaluation system, its recording medium and health degree evaluating method |
KR100794516B1 (en) * | 2007-12-03 | 2008-01-14 | 한국정보통신대학교 산학협력단 | System and method for diagnosis and clinical test selection using case based machine learning inference |
JP2014233611A (en) * | 2013-06-05 | 2014-12-15 | 株式会社東芝 | Treatment planning support apparatus and treatment planning support system |
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US12073943B2 (en) | 2019-12-31 | 2024-08-27 | Coreline Soft Co., Ltd. | Medical image analysis system and similar case retrieval system using quantitative parameters, and methods for the same |
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