Graduation Year

2003

Document Type

Thesis

Degree

M.S.C.S.

Degree Granting Department

Computer Science

Major Professor

Lawrence O. Hall, Ph.D.

Co-Major Professor

Dmitry B. Goldgof, Ph.D.

Committee Member

Eugene Fink, Ph.D.

Keywords

Expert System, Rule Based System, Breast Cancer

Abstract

A clinical trial is defined as a study conducted on a group of patients to determine the effect of a treatment. Assignment of patients to clinical trials is a data and labor intensive task. Usually, medical personnel manually check the eligibility of a patient for a clinical trial based on the patient's medical history and current medical condition. According to studies, most clinical trials are under-enrolled which negatively affects their effectiveness. We have developed web-based agents that can test the eligibility of patients for many clinical trials at once. We have tested various heuristics for optimizing cost and data entry needed in assigning patients to clinical trials. Testing eligibility of a patient for many clinical trials is only feasible if it is cost and data entry efficient. Agents with different heuristics were then tested on data from current breast cancer patients at the Moffitt Cancer Center. Results with different heuristics are compared with each other and with that of the clinicians. It is shown that cost savings are possible in clinical trial assignment. Also, less data entry is needed when probabilistic agents are used to reorder questions.

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