AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation

Joshi, S., Urteaga, I., van Amsterdam, W. A. C., Hripcsak, G., Elias, P., Recht, B., Elhadad, N., Fackler, J., Sendak, M. P., Wiens, J., Deshpande, K., Wald, Y., Fiterau, M., Lipton, Z., Malinsky, D., Nayan, M., Namkoong, H., Park, S., Vogt, J. E., & Ranganath, R. (2025). AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation. Journal of the American Medical Informatics Association, 32(3), 589–594. https://doi.org/10.1093/jamia/ocae301
Authors:
Shalmali Joshi
Iñigo Urteaga
Wouter A. C Van Amsterdam
George Hripcsak
Pierre Elias
Benjamin Recht
Noémie Elhadad
James Fackler
Mark P Sendak
Jenna Wiens
Kaivalya Deshpande
Yoav Wald
Madalina Fiterau
Zachary Lipton
Daniel Malinsky
Madhur Nayan
Hongseok Namkoong
Soojin Park
Julia E. Vogt
Rajesh Ranganath
Affiliated Authors:
Shalmali Joshi
George Hripcsak
Pierre Elias
Noémie Elhadad
Daniel Malinsky
Soojin Park
Author Keywords:
artificial intelligence
causal inference
healthcare
Publication Type:
Article
Unique ID:
10.1093/jamia/ocae301
PMID:
Publication Date:
Data Source:
Scopus

Record Created: