Table of Contents
Collecting and Interpreting Temporal Data in an Expert System
Introduction
Heart Disease Program
State of example case to be diagnosed
Temporal properties of data
Temporal patterns needed
Physician enters case:
Physician adds details
Physician describes chest pain
Temporal menus needed to capture patient state
PPT Slide
Intervals determined by HDP
Challenges interpreting descriptions
Temporal boundary knowledge
Findings indicating a progressive disease appear in several ways
Defaults are needed to fill in the data the user leaves unspecified
Defaults can lead to mistakes
PPT Slide
HDP diagnosis
Future directions
References
PPT Slide
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Author: Bill Long
Email: wjl@mit.edu
Home Page: /people/wjl/
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