Adaptive Information Extraction from Clinical Patient Records

Among the applications of computer science in the field of health care and biomedicine, the processing of clinical patient records is one of the increasingly important topics for improving the Electronic Health Records (EHR) systems. A practical use of EHR systems is to help improve the decision making process for the physicians. The goal of this project is to develop an information extraction tool that extracts the relevant information with respect to the patient disease/symptoms, which help the physicians in their decision making process. In order to extract the relevant information with respect to diseases, we plan to cluster the patient’s records into groups according to their diseases and symptoms, and apply data mining tools to discover meaningful patterns per group. Patterns could refer to procedures or surgeries, frequent symptoms; treatments related diseases associated with specific diseases. The usefulness of such tool is primary based on recommending a list of….tobecontinued

Faculty Supervisor:

Jimmy Huang

Student:

Partner:

Alpha Global IT

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

York University

Program: