sj-xlsx-2-dhj-10.1177_20552076221089099 - Supplemental material for Artificial intelligence and medical education: A global mixed-methods study of medical students’ perspectives

Supplemental material, sj-xlsx-2-dhj-10.1177_20552076221089099 for Artificial intelligence and medical education: A global mixed-methods study of medical students’ perspectives by Hamza Ejaz, Hari McGrath, Brian LH Wong, Andrew Guise, Tom Vercauteren and Jonathan Shapey in Digital Health

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Bibliographische Detailangaben
Hauptverfasser:	Ejaz, Hamza, McGrath, Hari, Wong, Brian LH, Guise, Andrew, Vercauteren, Tom, Shapey, Jonathan
Format:	Dataset
Sprache:	eng
Schlagworte:	Aged Health Care Anthropology Cardiology Cultural Studies not elsewhere classified Endocrinology Engineering not elsewhere classified FOS: Clinical medicine FOS: Computer and information sciences FOS: Economics and business FOS: Health sciences FOS: Other engineering and technologies FOS: Other humanities FOS: Political science FOS: Sociology Geriatrics and Gerontology Health and Community Services Information and Computing Sciences not elsewhere classified Nursing not elsewhere classified Oncology and Carcinogenesis not elsewhere classified Organisation and Management Theory Public Health and Health Services not elsewhere classified Science Policy Social Policy Sociology
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Beschreibung
Zusammenfassung:	Supplemental material, sj-xlsx-2-dhj-10.1177_20552076221089099 for Artificial intelligence and medical education: A global mixed-methods study of medical students’ perspectives by Hamza Ejaz, Hari McGrath, Brian LH Wong, Andrew Guise, Tom Vercauteren and Jonathan Shapey in Digital Health
DOI:	10.25384/sage.19695041