A Bayesian approach for detecting a disease that is not being modeled

Aronis, John M.; Ferraro, Jeffrey P.; Gesteland, Per H.; Tsui, Fuchiang; Ye, Ye; Wagner, Michael M.; Cooper, Gregory F.

A patient’s chief complaint is a concise statement of the symptom or problem that caused the patient to seek medical care. Often stated in the patient’s own words, a chief complaint typically does not mention predefined syndromes or disease categories. Keyword-based systems can operate in real-time to identify anomalies or clusters of unusual findings from text [11]. [12] describes a semantic scan sytem that infers a set of topics (probability distributions over words) from the free-text of chief complaints. The system learns one set of topics using past data and a second set of topics from the most recent 3-hour moving window, assigns each patient case to its most likely topic, then looks for anomalous counts and clusters of topics. [13] extends this approach to identify clusters also based on geography or social patterns.