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Artificial Intelligence in Health Profession Education.

Avinash Supe1, Chinmay Shah2

  • 1Department of Surgical Gastroenterology and Medical Education, Seth G S Medical College, Mumbai, Maharashtra, 400012, India. avisupe2@gmail.com.

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Artificial Intelligence (AI) integration in medicine requires Health Professional Education (HPE) to develop AI literacy. Responsible AI adoption in healthcare necessitates addressing ethical concerns and focusing on augmenting, not replacing, clinical judgment.

Keywords:
AIAssessmentClinical decisionEthical issuesHPELearningTeaching

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Area of Science:

  • Medical Education
  • Artificial Intelligence
  • Healthcare Technology

Background:

  • Artificial Intelligence (AI) is rapidly transforming healthcare, impacting diagnostics, patient outcomes, and care delivery.
  • AI also offers benefits in medical research, such as accelerated drug discovery and advanced data analysis.
  • The integration of AI into medicine necessitates preparing future clinicians through Health Professional Education (HPE).

Purpose of the Study:

  • To highlight the critical need for AI literacy in Health Professional Education (HPE).
  • To discuss the transformative potential and inherent challenges of AI in healthcare.
  • To advocate for responsible AI adoption in medical practice and education.

Main Methods:

  • Literature review of AI applications in healthcare and education.
  • Analysis of ethical, technical, and practical challenges associated with AI implementation.
  • Synthesis of recommendations for curriculum development in HPE regarding AI.

Main Results:

  • AI enhances diagnostics, predicts outcomes, and streamlines administrative tasks in healthcare.
  • AI enables personalized learning and simulation training in education.
  • Significant challenges include data privacy, algorithmic bias, ethical accountability, and technical implementation hurdles.

Conclusions:

  • Health Professional Education (HPE) must integrate AI literacy to prepare clinicians for AI-augmented healthcare.
  • Responsible AI adoption requires robust curricula addressing ethical use, transparency, and limitations.
  • AI should serve as a tool to augment clinical intelligence and improve workflows, emphasizing human judgment and strong regulation.