Esdiabetes (an expert system in diabetes)

Authors:
Mario A. Garcia;Amit J. Gandhi;Tinu Singh;Leo Duarte;Rui Shen;Maruthi Dantu;Steve Ponder;Hilda Ramirez
Affiliations:
Texas A&M University, Corpus Christi, 6300, Ocean Drive;Texas A&M University, Corpus Christi, 6300, Ocean Drive;Texas A&M University, Corpus Christi, 6300, Ocean Drive;Texas A&M University, Corpus Christi, 6300, Ocean Drive;Texas A&M University, Corpus Christi, 6300, Ocean Drive;Texas A&M University, Corpus Christi, 6300, Ocean Drive;Texas A&M University, Corpus Christi, 6300, Ocean Drive;Texas A&M University, Corpus Christi, 6300, Ocean Drive
Venue:
Proceedings of the seventh annual consortium for computing in small colleges central plains conference on The journal of computing in small colleges
Year:
2001

Citing 3
Cited 0

Introduction to expert systems

Introduction to expert systems
Artificial Intelligence in Medicine: Expert Systems

Artificial Intelligence in Medicine: Expert Systems
Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley series in artificial intelligence)

Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley series in artificial intelligence)

Quantified Score

Hi-index	0.00

Visualization

Abstract

Diabetes is a disease that affects many people in the world [1]. Diabetes cost in the U.S.A. is estimated to represent 5.8% of total personal health-care expenditures. In Europe diabetes is estimated to consume about 10% of the total health care budget Patients with diabetes need to maintain a normal blood glucose level. ESDIABETES, was developed by computer science graduate students at Texas A&M University Corpus Christi to help people monitor and control the blood glucose level. The diabetes experts were Dr. Steve Ponder and Dr. Hilda Ramirez from Dricoll's children hospital. This paper describes the steps followed to implement ESDIABETES.