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Patient Participation in AI for Health Curriculum.

Kirsten Ostherr1, Waverly Huang1, Ana Park2

  • 1Medical Humanities Research Institute, Rice University, Houston, TX, United States.

Journal of Participatory Medicine
|September 24, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) in healthcare lacks patient perspectives in its responsible use education. This viewpoint proposes integrating patient insights into premedical training to ensure patient-centered AI in healthcare.

Keywords:
artificial intelligencecoproduction of knowledgeethicsexperts by experiencepatient perspectivespremedical education

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Area of Science:

  • Healthcare innovation
  • Medical education
  • Artificial intelligence ethics

Background:

  • Healthcare AI adoption outpaces clinical workforce education on responsible use.
  • Existing AI guidance lacks crucial patient perspectives, creating an information gap.
  • Patient viewpoints are vital for defining and ensuring responsible AI in healthcare.

Purpose of the Study:

  • To address the gap in patient perspectives within healthcare AI education.
  • To propose a novel method for integrating patient insights into undergraduate premedical curricula.
  • To foster an inclusive and patient-centered future for AI in health care.

Main Methods:

  • A viewpoint discussion coauthored by patients, students, and faculty.
  • Focus on integrating patient perspectives into US undergraduate premedical education.
  • Developing a framework for patient-centered AI in health care.

Main Results:

  • Identified a significant gap in patient involvement in healthcare AI guidelines and education.
  • Proposed a concrete approach to incorporate patient perspectives into premedical training.
  • Highlighted the value of patient insights for responsible AI development.

Conclusions:

  • Integrating patient perspectives into premedical education is essential for responsible healthcare AI.
  • This approach can cultivate future clinicians who prioritize patient-centered AI.
  • Addressing this educational gap is key to an ethical and trustworthy AI future in medicine.