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An artificial intelligence system to predict progression of immune dysfunction in healthy older patients
E M Mahler1, R M Schmidt, V I Kvitash
1Center for Preventive Medicine and Health Research, California Pacific Medical Center, San Francisco.
Abstract:
In 1983, forty nine participants returning for their annual HEALTH WATCH evaluation were assessed for immune function status and served as healthy controls in an early study of "normal" reference values for T4 and T8 lymphocyte counts and T4/T8 lymphocyte ratios, B lymphocyte counts, and other laboratory tests for immune function then available. Balascopy, a computer-assisted pattern recognition system for detection, quantification and cognition of multiple imbalances among clinical laboratory and health behavioral parameters, facilitates identification of otherwise healthy individuals with evidence of early immune dysfunction. When the T4 and T8 immunology tests were combined with 7 health index behavioral subscores, and 24 routine clinical laboratory tests, we are able to obtain a bodyprint unique for each patient, providing a comprehensive health status profile specific for that individual. These bodyprints serve as tools for the evaluation of otherwise undetectable metabolic, immunological and behavioral imbalances in a given patient in an unprecedented individualized manner. We show here a longitudinal look at a balascopic evaluation of one patient who has evidence of progressive immune dysfunction with development of only mild clinical symptoms.

