AI in Healthcare Short Course

This hands-on short course introduces healthcare professionals and stakeholders to how artificial intelligence can improve clinical decision-making, operational efficiency, and patient outcomes. Covering core concepts in machine learning and data science applied to health settings, the course walks through clinical data types, data governance and privacy (HIPAA/GDPR considerations), model development lifecycle, evaluation metrics relevant to healthcare, and common AI techniques such as predictive risk modeling, medical image analysis, and NLP for clinical text. Practical labs use realistic, de-identified examples to demonstrate data preprocessing, model training, validation, and interpretation (including explainability methods), plus a deployment overview for integrating AI into clinical workflows and health IT systems.

Ethics, bias, safety, and regulatory considerations are emphasized throughout, with case studies highlighting risks, mitigation strategies, and the importance of clinical validation and multidisciplinary collaboration. By the end, participants will understand when AI is appropriate in healthcare, how to assess model performance and limitations, and the steps needed to pilot or implement safe, compliant AI solutions—equipping clinicians, managers, and technical teams to pursue responsible AI projects in their organizations. To register click the following link https://docs.google.com/forms/d/1g7dl9iKGPSm88Bhq1ot7OGZ_NvrXyAX1-9IatqW_xhg/preview