Mechanistic interpretability of reinforcement learning in Medicaid care coordination

Mechanistic interpretability transforms opaque algorithmic assistance into auditable decision support, providing a governance scaffold for clinical artificial intelligence deployment.

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Publication Details

Journal
BMJ Health & Care Informatics
Published
2026-02-01
DOI
https://doi.org/10.1136/bmjhci-2025-101935
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Mechanistic interpretability of reinforcement learning in Medicaid care coordination

Rajaie Batniji, Parth Sheth, S Basu, Aakriti Kinra et al.
BMJ Health & Care Informatics
Adversarial Robustness in Machine Learning
article

Mechanistic interpretability of reinforcement learning in Medicaid care coordination

Rajaie Batniji, Parth Sheth, S Basu, Aakriti Kinra, Bhairavi Muralidharan, Namrata Elamaran, Sadiq Patel
article en

Abstract

Mechanistic interpretability transforms opaque algorithmic assistance into auditable decision support, providing a governance scaffold for clinical artificial intelligence deployment.

BMJ Health & Care InformaticsVol. 33(1)
Benchmark Research (United States) (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 62%
Adversarial Robustness in Machine Learning
DOIOpen Access PDFOpenAlex
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