Our research focuses on a number of state-of-the-art technologies across multiple specializations to extract actionable information from clinician-patient interactions – Critical data which can then be disseminated to the patient and clinical care team. 




Based on the exciting findings from MIT's Collaborative Data Science in Medicine. In DeepLEAP, we analyze physicians' notes to extract goals of care conversations between the clinical care team and the patient.

Patient symptoms are incredibly difficult to discern from structured data. We've developed methods to extract and present the documentation of patient symptoms from within clinicians' notes.


Utilizing audio from real clinician-patient conversations, we aim to capture the most precise patient care preferences.