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CRETIC: Optimizing Clinical Reasoning in Time-Critical Scenarios: A data-driven multimodal approach´s Profile image

CRETIC: Optimizing Clinical Reasoning in Time-Critical Scenarios: A data-driven multimodal approach

Project
01.09.2024 - 31.08.2028
School of Computing, Faculty of Science, Forestry and Technology

Funders

Main funder

CRETIC: Optimizing Clinical Reasoning in Time-Critical Scenarios: A data-driven multimodal approach funder logo

Leaders

CRETIC aims to optimize emergency training of healthcare students and trainees. We will develop an innovative gamified platform that combines virtual patients and elements of educational escape rooms to simulate clinical emergencies. Data from multiple sources (physiological sensors, questionnaires and digital logs) will be collected to capture the full breadth of the dynamics of the clinical reasoning process. The data will be analyzed using the latest temporal learning analytics and explainable artificial intelligence methods to map the clinical reasoning process and the factors that lead to successful and effective decision-making. The proposal will result in an open scalable platform that will dramatically improve the training of medical emergencies, offer personalized insights into effective decision-making, provide a safe environment for practicing challenging clinical situations, and ultimately decrease medical errors, one of the leading causes of death worldwide

Cooperation

Keywords