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We evaluate MedLog across four clinical deployments spanning intensive care monitoring, infectious disease severity prediction, hospital quality reporting, and patient attendance prediction. MedLog makes model behavior visible in practice. It reveals patterns that offline evaluation does not capture, including temporal failure modes, workflow-dependent variability, interactions between model outputs and clinician behavior, and performance degradation during severe weather events.

Bern, Switzerland

A prospective three-month pilot monitoring the BEACON early-warning model in the ICU at the University Hospital of Bern, generating early warnings of circulatory and respiratory failure.

Ho Chi Minh City, Vietnam

Monitoring an AI model that predicts tetanus progression from wearable physiological waveforms at the Hospital for Tropical Diseases.

San Diego, USA

Logging a deployed LLM system for automated SEP-1 sepsis quality reporting at UC San Diego Health.

New York, USA

Population-scale monitoring of a patient-attendance prediction model across the Mount Sinai Health System.
LocationDurationNumber of patientsMedian age (IQR)No. MedLog records
Bern, Switzerland114 days212 (148 M, 64 F)68.00 (55.80 – 77.00)223,840
Ho Chi Minh City, Vietnam289 days15 (14 M, 1 F)49.94 (47.03 – 60.54)3,406
San Diego, California, USA89 days60 (28 M, 32 F)64.00 (54.00 – 71.25)3,766
New York, New York, USA244 days791,319 (324,294 M, 466,626 F, 399 O)54.00 (36.00 – 68.00)2,914,264