Automated patient/document identification and categorization for medical data

• US 8,751,495 B2
• Filed: 09/28/2010
• Issued: 06/10/2014
• Est. Priority Date: 09/29/2009
• Status: Active Grant

• Current Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Original Assignee: Siemens Medical Solutions USA Incorporated (Siemens AG)
• Inventors: Chung, Stanley, Farooq, Faisal, Fung, Glenn, Krishnapuram, Balaji, Rao, R. Bharat, Rosales, Romer E., Weis, John, Yu, Shipeng
• Primary Examiner(s): Chen, Susan
• Application Number:
  US12/891,983
• Publication Number:
  US 20110078145A1
• Time in Patent Office: 1,351 Days
• Field of Search: 707/713, 705/64, 704/1, 704/257, 706/12
• US Class Current: 707/737
• CPC Class Codes: G06F 16/313 Selection or weighting of terms for indexing
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A method, including receiving a data source selection from a user or software application, the data source including medical information of a plurality of patients, receiving, from the user or software application, a data pattern that is related to a concept to be explored in the data source, querying the data source to find information that approximately matches the data pattern; and receiving the information from the data source, wherein the information includes unstructured data, assigning a classification to individual parts of the information based on the part'"'"'s relationship to the data pattern, and outputting the classified information to the user or software application.

Claims

1. A method, comprising:

receiving a data source selection from a user or software application, the data source including medical information of a plurality of patients;

receiving, from the user or software application, a data pattern that is related to a concept to be explored in the data source;

querying the data source to find information that approximately matches the data pattern; and

receiving the information from the data source, wherein the information includes unstructured data, assigning a classification to individual parts of the information based on the part'"'"'s relationship to the data pattern; and

outputting the classified information, including the unstructured data as a table including a classification label and a passage header columns, to the user or software application, the passage column being of the unstructured data separated into the individual parts, the unstructured data of the passage column comprising fragment passages that are one or more sentences, one or more clauses, or one or more sentences and clauses, which include a query term and surrounding text, and the classification label indicating positive or negative or not applicable to support of corresponding passages of the passage column and

wherein the method is performed using a processor.

2. The method of claim 1, wherein the row further includes a link to the source containing the individual part of the information.

3. The method of claim 1, wherein the row further includes a numerical score indicating a strength of the classification.

4. The method of claim 1, further comprising grouping individual parts of the information in adjacent rows, wherein the grouping is based on similarity of the individual parts to each other.

5. The method of claim 1, wherein an unstructured data search algorithm is used to find the information that approximately matches the data pattern.

6. The method of claim 1, wherein the data source includes electronic medical records, radiological images, or gene sequences.

7. The method of claim 1, wherein the unstructured data includes text, or biological sequences.

8. The method of claim 1, wherein the classified information includes structured data.

9. The method of claim 1, wherein the concept is a medical question.

10. The method of claim 1, wherein the data pattern includes a keyword, regular expression or a context-free grammar.

11. The method of claim 1, wherein the data pattern includes an image part or an image filter.

12. The method of claim 1, wherein the data pattern includes genetic data.

13. The method of claim 1, wherein receiving the information comprises receiving the unstructured data for the plurality of patients, outputting comprises outputting the unstructured data for the plurality of patients in the table.

14. A system, comprising:

a memory device for storing a program;

a processor in communication with the memory device, the processor operative with the program to;

receive a data source selection, the data source including medical information of a plurality of patients;

receive a data pattern that is related to a concept to be explored in the data source;

query the data source to find information that approximately matches the data pattern; and

receive the information from the data source, wherein the information includes unstructured data, assign a classification to individual parts of the information based on the part'"'"'s relationship to the data pattern, and output the classified information, including the unstructured data in a table, the table being of the unstructured data separated into the individual parts, the unstructured data of the table comprising fragment passages that are one or more sentences, one or more clauses, or one or more sentences and clauses, which include a query term and surrounding text of a passage column header, and the classified information including a corresponding indication of in favor or against or not applicable to the data pattern in a classification label column header for each of the passages of the table.

15. The system of claim 14, wherein the processor is further operative with the program to display the output on a graphical user interface (GUI).

16. The system of claim 15, wherein the classified information is browsable, editable, or processible via the GUI.

17. A computer program product, comprising:

a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising;

computer readable program code configured to perform the acts of;

querying a data source to find data that exactly or approximately matches a data pattern, wherein the data source includes medical information of a plurality of patients; and

receiving the data from the data source, wherein the data includes unstructured data, assigning a classification or score to individual parts of the data based on the part'"'"'s relationship to the data pattern, and outputting the classified/scored data, including the unstructured data in a table, the table being of the unstructured data separated into the individual parts, the unstructured data of the table comprising fragment passages that are one or more sentences, one or more clauses, or one or more sentences and clauses, which include a query term and surrounding text of a passage column header in the table, and the classification or score of a classification label column header in the table including a corresponding indication of positive, negative or not applicable for each of the fragment passages in the table.

18. The computer program product of claim 17, wherein the data source or the data pattern is pre-determined.

19. The computer program product of claim 17, wherein the data pattern is determined from a concept, the concept being related to a medical question.