Accession Number : ADA306139
Title : Dynamic Aggregation of Symptom Data.
Descriptive Note : Final rept.,
Corporate Author : NAVAL HEALTH RESEARCH CENTER SAN DIEGO CA
Personal Author(s) : Angus, John E. ; Williamson, Robert ; Pick, Daniel ; Ames, Kevin ; Niknejad, Amir
PDF Url : ADA306139
Report Date : JUL 1996
Pagination or Media Count : 42
Abstract : The health and well-being of U.S. service personnel assigned to duty in foreign countries is of vital importance to the successful completion of the intended missions. Upon relocation, such groups represent nonindigenous populations exposed to the endemic diseases of the region and other hazards associated with the assignment. Field epidemiologists and preventive medical specialists need ways to obtain and assess clinical data as quickly and accurately as possible and to relate the various signs and symptoms at the time of presentation into associated categories to support early detection of disease and illness. The objective of this study was to develop a computerized algorithm that would accept, sequentially in real time, patient symptom vectors and dynamically identity patterns of probable syndromes/diseases. The approach taken in this study was that provided by Adaptive Resonance Theory (ART). A simple ART algorithm was developed that was capable of sequentially accepting patient symptom vectors and dynamically clustering them into patterns or syndromes described by prototype symptom vectors. The basic ART algorithm was demonstrated with simulated symptom data from 300 patients representing 10 underlying syndromes. The algorithm was shown to correctly identify the syndromes and to cluster the patients into their correct syndromes.
Descriptors : *DISEASES, *SIGNS AND SYMPTOMS, *MEDICAL SERVICES, *MEDICAL PERSONNEL, ALGORITHMS, MILITARY PERSONNEL, NATIONS, DETECTION, FOREIGN, MILITARY FORCES(FOREIGN), HAZARDS, REAL TIME, THEORY, PROBABILITY, CLINICAL MEDICINE, TIME, MEDICINE, MISSIONS, RESONANCE, ADAPTIVE SYSTEMS, ACTIVE DUTY, COMPUTER APPLICATIONS, RELOCATION, SPECIALISTS, PHYSICIANS, PREVENTION, EPIDEMIOLOGY.
Subject Categories : Medicine and Medical Research
Distribution Statement : APPROVED FOR PUBLIC RELEASE