Artificial Intelligence vs Clinician Performance in Estimating Probabilities of Diagnoses Before and After Testing

Adam Rodman; Thomas A Buckley; Arjun K Manrai; Daniel J Morgan

doi:10.1001/jamanetworkopen.2023.47075

Artificial Intelligence vs Clinician Performance in Estimating Probabilities of Diagnoses Before and After Testing

JAMA Netw Open. 2023 Dec 1;6(12):e2347075. doi: 10.1001/jamanetworkopen.2023.47075.

Authors

Adam Rodman¹, Thomas A Buckley², Arjun K Manrai³, Daniel J Morgan^{4

5}

Affiliations

¹ Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts.
² Department of Computer Science, University of Massachusetts, Amherst, Massachusetts.
³ Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts.
⁴ Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore.
⁵ Veterans Affairs Maryland Healthcare System, Baltimore.

No abstract available

Plain language summary

This diagnostic study compares the performance of artificial intelligence (AI) with that of human clinicians in estimating the probability of diagnoses before and after testing.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Artificial Intelligence*
Diagnosis*
Humans
Physicians*

Grants and funding

K01 HL138259/HL/NHLBI NIH HHS/United States