This predictor addresses the problem that rare-disease patients are often assessed intermittently, while clinically important deterioration develops continuously between visits.
The model combines sparse disease knowledge with each patient’s longitudinal physiological data to estimate where they are on their disease trajectory now, forecast plausible near-term futures, and identify when the risk of a meaningful clinical event is rising early enough to act.
The following is the HTML simulator using synthetic patients for 5 rare diseases:
HTML Simulator: