Christopher Fields
he/him/his
Associate Research ScientistAbout
Research
Publications
2026
External validation improves generalizability, replicability and reproducibility in predictive models for neuroimaging
Rosenblatt M, Foster M, Adkinson B, Tejavibulya L, Khaitova M, Ye J, Sun H, Rodriguez R, Camp C, Chinta A, McCusker M, Han L, Fields C, Mehta S, Scheinost D. External validation improves generalizability, replicability and reproducibility in predictive models for neuroimaging. Nature Methods 2026, 1-11. PMID: 42203860, DOI: 10.1038/s41592-026-03115-9.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsWhat marks the “ideal” black doctor? a critical discourse analysis of flexnerian segregation within contemporary diversity discourses
Black C, Konopasky A, Temple S, Sukhera J, Okolo J, Gray A, Funaro M, Fields C. What marks the “ideal” black doctor? a critical discourse analysis of flexnerian segregation within contemporary diversity discourses. Advances In Health Sciences Education 2026, 1-33. PMID: 42030013, DOI: 10.1007/s10459-026-10541-z.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus Statements
2025
Who Are Flexnerian-Deprived Black Americans? A Quantitative Analysis of Historical Representation Within American Medical Education
Black C, Littlejohn J, Clarke A, Overton K, Hoskins T, Pierre-Louis D, Owusu P, Gray A, Fields C, Sukhera J, Konopasky A. Who Are Flexnerian-Deprived Black Americans? A Quantitative Analysis of Historical Representation Within American Medical Education. Journal Of Racial And Ethnic Health Disparities 2025, 1-15. PMID: 41196502, DOI: 10.1007/s40615-025-02699-w.Peer-Reviewed Original ResearchBeyond Race-Based Ideology in HPE DEI Attempts: A Framework and Vocabulary for Sociohistorical Justice
Black C, Brinker M, Acquaye A, Fields C, Temple S, Huggins L, Konopasky A. Beyond Race-Based Ideology in HPE DEI Attempts: A Framework and Vocabulary for Sociohistorical Justice. Teaching And Learning In Medicine 2025, 37: 480-494. PMID: 40760971, DOI: 10.1080/10401334.2025.2521473.Peer-Reviewed Original ResearchLongitudinal and Geographic Trends in Perceived Racial Discrimination Among Adolescents in the United States: The Adolescent Brain Cognitive Development Study
Fields C, Black C, Calhoun A, Rosenblatt M, Rodriguez R, Aina J, Thind J, Grayson J, Khalifa F, Assari S, Zhou X, Nagata J, Gee D. Longitudinal and Geographic Trends in Perceived Racial Discrimination Among Adolescents in the United States: The Adolescent Brain Cognitive Development Study. Journal Of Adolescent Health 2025, 77: 118-127. PMID: 40382724, DOI: 10.1016/j.jadohealth.2025.03.014.Peer-Reviewed Original ResearchGovernance for anti-racist AI in healthcare: integrating racism-related stress in psychiatric algorithms for Black Americans
Fields C, Black C, Thind J, Jegede O, Aksen D, Rosenblatt M, Assari S, Bellamy C, Anderson E, Holmes A, Scheinost D. Governance for anti-racist AI in healthcare: integrating racism-related stress in psychiatric algorithms for Black Americans. Frontiers In Digital Health 2025, 7: 1492736. PMID: 40444183, PMCID: PMC12119476, DOI: 10.3389/fdgth.2025.1492736.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus Statements
2024
Sociohistorical justice: a corrective framework to mend the modern harms of medical history
Black C, Temple S, Acquaye A, Fields C, Konopasky A. Sociohistorical justice: a corrective framework to mend the modern harms of medical history. The Lancet Regional Health - Americas 2024, 38: 100874. PMID: 39262427, PMCID: PMC11387348, DOI: 10.1016/j.lana.2024.100874.Peer-Reviewed Original ResearchBridging Species and Disciplines: Incorporating Sociological Frameworks into Animal Models of Addiction
Fields C (2024) Bridging Species and Disciplines: Incorporating Sociological Frameworks into Animal Models of Addiction. In Dr. PA Rojo and Dr. E Martínez-Laorden (Eds.), Multidisciplinary Approach for Better Understanding of Addictive Behaviour. IntechOpen. DOI:10.5772/intechopen.114874.ChaptersA comparison of machine learning methods for quantifying self-grooming behavior in mice
Correia K, Walker R, Pittenger C, Fields C. A comparison of machine learning methods for quantifying self-grooming behavior in mice. Frontiers In Behavioral Neuroscience 2024, 18: 1340357. PMID: 38347909, PMCID: PMC10859524, DOI: 10.3389/fnbeh.2024.1340357.Peer-Reviewed Original ResearchA Comparison of Machine Learning Methods for Quantifying Self-Grooming Behavior in Mice.
Correia K, Walker R, Pittenger C and Fields C (2024) A comparison of machine learning methods for quantifying self-grooming behavior in mice. Front. Behav. Neurosci. 18:1340357. doi: 10.3389/fnbeh.2024.1340357Peer-Reviewed Original Research