The Cases for and against Artificial Intelligence in the Medical School Curriculum

doi:10.1148/ryai.220074

. 2022 Aug 17;4(5):e220074.

doi: 10.1148/ryai.220074. eCollection 2022 Sep.

The Cases for and against Artificial Intelligence in the Medical School Curriculum

Brandon Ngo¹, Diep Nguyen¹, Eric vanSonnenberg¹

Affiliations

PMID: 36204540
PMCID: PMC9530767
DOI: 10.1148/ryai.220074

The Cases for and against Artificial Intelligence in the Medical School Curriculum

Brandon Ngo et al. Radiol Artif Intell. 2022.

. 2022 Aug 17;4(5):e220074.

doi: 10.1148/ryai.220074. eCollection 2022 Sep.

Authors

Brandon Ngo¹, Diep Nguyen¹, Eric vanSonnenberg¹

Affiliation

¹ University of Arizona College of Medicine - Phoenix, HSEB C536, 475 N 5th St, Phoenix, AZ 85004.

PMID: 36204540
PMCID: PMC9530767
DOI: 10.1148/ryai.220074

Abstract

Although artificial intelligence (AI) has immense potential to shape the future of medicine, its place in undergraduate medical education currently is unclear. Numerous arguments exist both for and against including AI in the medical school curriculum. AI likely will affect all medical specialties, perhaps radiology more so than any other. The purpose of this article is to present a balanced perspective on whether AI should be included officially in the medical school curriculum. After presenting the balanced point-counterpoint arguments, the authors provide a compromise. Keywords: Artificial Intelligence, Medical Education, Medical School Curriculum, Medical Students, Radiology, Use of AI in Education © RSNA, 2022.

Keywords: Artificial Intelligence; Medical Education; Medical School Curriculum; Medical Students; Radiology; Use of AI in Education.

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Conflict of interest statement

Disclosures of conflicts of interest: B.N. No relevant relationships. D.N. No relevant relationships. E.v.S. No relevant relationships.

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References

1. Paranjape K , Schinkel M , Nannan Panday R , Car J , Nanayakkara P . Introducing artificial intelligence training in medical education . JMIR Med Educ 2019. ; 5 ( 2 ): e16048 . - PMC - PubMed
1. Savage TR . Artificial intelligence in medical education . Acad Med 2021. ; 96 ( 9 ): 1229 – 1230 . - PubMed
1. McCoy LG , Nagaraj S , Morgado F , Harish V , Das S , Celi LA . What do medical students actually need to know about artificial intelligence? NPJ Digit Med 2020. ; 3 ( 1 ): 86 . - PMC - PubMed
1. Santomartino SM , Yi PH . Systematic Review of Radiologist and Medical Student Attitudes on the Role and Impact of AI in Radiology . Acad Radiol 2022. . 10.1016/j.acra.2021.12.032. Published online January 29, 2022. - DOI - PubMed
1. National Resident Matching Program (NRMP). Main Residency Match Data and Reports . https://www.nrmp.org/match-data-analytics/residency-data-reports/. Published March 18, 2022. Accessed May 28, 2022 .

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[1] Paranjape K , Schinkel M , Nannan Panday R , Car J , Nanayakkara P . Introducing artificial intelligence training in medical education . JMIR Med Educ 2019. ; 5 ( 2 ): e16048 . - PMC - PubMed

[2] Paranjape K , Schinkel M , Nannan Panday R , Car J , Nanayakkara P . Introducing artificial intelligence training in medical education . JMIR Med Educ 2019. ; 5 ( 2 ): e16048 . - PMC - PubMed

[3] Savage TR . Artificial intelligence in medical education . Acad Med 2021. ; 96 ( 9 ): 1229 – 1230 . - PubMed

[4] Savage TR . Artificial intelligence in medical education . Acad Med 2021. ; 96 ( 9 ): 1229 – 1230 . - PubMed

[5] McCoy LG , Nagaraj S , Morgado F , Harish V , Das S , Celi LA . What do medical students actually need to know about artificial intelligence? NPJ Digit Med 2020. ; 3 ( 1 ): 86 . - PMC - PubMed

[6] McCoy LG , Nagaraj S , Morgado F , Harish V , Das S , Celi LA . What do medical students actually need to know about artificial intelligence? NPJ Digit Med 2020. ; 3 ( 1 ): 86 . - PMC - PubMed

[7] Santomartino SM , Yi PH . Systematic Review of Radiologist and Medical Student Attitudes on the Role and Impact of AI in Radiology . Acad Radiol 2022. . 10.1016/j.acra.2021.12.032. Published online January 29, 2022. - DOI - PubMed

[8] Santomartino SM , Yi PH . Systematic Review of Radiologist and Medical Student Attitudes on the Role and Impact of AI in Radiology . Acad Radiol 2022. . 10.1016/j.acra.2021.12.032. Published online January 29, 2022. - DOI - PubMed

[9] National Resident Matching Program (NRMP). Main Residency Match Data and Reports . https://www.nrmp.org/match-data-analytics/residency-data-reports/. Published March 18, 2022. Accessed May 28, 2022 .

[10] National Resident Matching Program (NRMP). Main Residency Match Data and Reports . https://www.nrmp.org/match-data-analytics/residency-data-reports/. Published March 18, 2022. Accessed May 28, 2022 .

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The Cases for and against Artificial Intelligence in the Medical School Curriculum

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The Cases for and against Artificial Intelligence in the Medical School Curriculum

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