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OpenLearning

Advanced AI Training for Medical Students

via OpenLearning

Overview

Master AI & Machine Learning for 50% Off
Go under the hood of AI — neural networks, real-world applications & more. Designed by UNSW experts.
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This course develops practical AI literacy for medical students across study, clinical placements, examinations, research, and career planning. It emphasizes verification, independent clinical reasoning, patient privacy, academic integrity, research reliability, and awareness of medico-legal risks.

Syllabus

  • Apply practical AI literacy skills across study, clinical placements, examinations, research, and career planning while maintaining academic integrity, patient safety, and independent clinical reasoning.
  • Apply AI-powered study tools using the TRACE verification framework to enhance learning while maintaining academic integrity and identifying AI hallucinations in medical content.
  • Evaluate AI-generated clinical outputs encountered during ward placements, maintain independent clinical reasoning, and uphold patient privacy obligations in AI-enabled hospital environments.
  • Implement structured AI-assisted exam preparation strategies using the 50/30/20 balanced model while recognising the risks of AI-dependency on OSCE and clinical examination performance.
  • Analyse AI-powered research tools for reliability, apply reference verification protocols to detect fabricated citations, and adhere to institutional and journal AI disclosure standards in academic writing.
  • Analyse AI-powered research tools for reliability, apply reference verification protocols to detect fabricated citations, and adhere to institutional and journal AI disclosure standards in academic writing.
  • Design a personal AI literacy development plan that addresses specialty-specific AI disruption, builds an AI-literate professional profile, and incorporates awareness of the medico-legal landscape for junior doctor.

Taught by

Eshwar Madas

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