1500 E. Medical Center Drive, B1220TC
Ann Arbor, MI 48109-5301
Available to mentor
Dr. Maxwell Spadafore is a Clinical Assistant Professor in the Department of Emergency Medicine. He completed his undergraduate degree in Life Science Informatics at the University of Michigan and graduated from the University of Michigan Medical School before completing his residency in Emergency Medicine at Michigan Medicine. Dr. Spadafore’s research expertise lies in the application of Artificial Intelligence and Machine Learning to medical education. He focuses particularly on using AI to improve learner assessment quality. He has been recognized nationally for his presentation skills and medical education research. In addition to his clinical role, he currently serves as the Director of Educational Informatics for the Office of Medical Student Education.
Administrative Contact:
Marlon Frazier
[email protected]
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ResidencyUniversity of Michigan, Department of Emergency Medicine, 2024
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Chief ResidentUniversity of Michigan, Department of Emergency Medicine, 2024
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MDUniversity of Michigan Medical School, Ann Arbor, 2020
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BS, Life Sciences InformaticsUniversity of Michigan Medical School, Ann Arbor, 2016
Application of machine learning and natural language processing to datasets in medical education to improve feedback quality and equity
Algorithmic bias and ethical design of machine learning in medical education
Development of novel metrics for resident performance evaluation using electronic health record data
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Bhanvadia S, Radha Saseendrakumar B, Guo J, Spadafore M, Daniel M, Lander L, Baxter SL. BMC Med Educ, 2024 Mar 15; 24 (1): 295Journal ArticleEvaluation of bias and gender/racial concordance based on sentiment analysis of narrative evaluations of clinical clerkships using natural language processing.
DOI:10.1186/s12909-024-05271-y PMID: 38491461 -
Spadafore M, Yilmaz Y, Rally V, Chan TM, Russell M, Thoma B, Singh S, Monteiro S, Pardhan A, Martin L, Monrad SU, Woods R. Acad Med, 2024 May 1; 99 (5): 534 - 540.Journal ArticleUsing Natural Language Processing to Evaluate the Quality of Supervisor Narrative Comments in Competency-Based Medical Education.
DOI:10.1097/ACM.0000000000005634 PMID: 38232079 -
Thoma B, Spadafore M, Sebok-Syer SS, George BC, Chan TM, Krumm AE. Acad Med, 2024 Apr 1; 99 (4S Suppl 1): S77 - S83.Journal ArticleConsidering the Secondary Use of Clinical and Educational Data to Facilitate the Development of Artificial Intelligence Models.
DOI:10.1097/ACM.0000000000005605 PMID: 38109656 -
Marcotte K, Negrete Manriquez JA, Hunt M, Spadafore M, Perrone KH, Zhou CY. Acad Med, 2024 Apr 1; 99 (4S Suppl 1): S25 - S29.Journal ArticleTrainees' Perspectives on the Next Era of Assessment and Precision Education.
DOI:10.1097/ACM.0000000000005602 PMID: 38109651 -
2024 Feb;PresentationLeveraging Electronic Health Records and Novel Analytics for Trainee Assessment
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Gordon M, Daniel M, Ajiboye A, Uraiby H, Xu NY, Bartlett R, Hanson J, Haas M, Spadafore M, Grafton-Clarke C, Gasiea RY, Michie C, Corral J, Kwan B, Dolmans D, Thammasitboon S. Med Teach, 2024 Apr; 46 (4): 446 - 470.Journal ArticleA scoping review of artificial intelligence in medical education: BEME Guide No. 84.
DOI:10.1080/0142159X.2024.2314198 PMID: 38423127 -
Spadafore M. 2023Additional ScholarshipDemonstration platform for feedback assessment artificial intelligence algorithm; http://commentquality.com
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Khamees D, Peterson W, Patricio M, Pawlikowska T, Commissaris C, Austin A, Davis M, Spadafore M, Griffith M, Hider A, Pawlik C, Stojan J, Grafton-Clarke C, Uraiby H, Thammasitboon S, Gordon M, Daniel M. Med Teach, 2022 May; 44 (5): 466 - 485.Journal ArticleRemote learning developments in postgraduate medical education in response to the COVID-19 pandemic - A BEME systematic review: BEME Guide No. 71.
DOI:10.1080/0142159X.2022.2040732 PMID: 35289242
