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Exploring clinical decision making

Data driven study

Large datasets from healthcare systems are analyzed to address important challenges in fields like clinical decision-making, resource optimization, and predictive analytics. State-of-the-art ML algorithms like DL are combined with NLP and traditional statistical learning

Computer lab

The computer lab uses simulated cases and advanced tools to study clinical decisions. Clinicians provide rationales evaluated by ML, NLP and LLMs. AI then discusses choices. By simulating healthcare, this environment examines cognition and pilots interventions. The goal is enhancing technology support for real patient care through decision research

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