The Clinical AI Value Alignment lab studies artificial intelligence (AI) used in healthcare settings. We focus on algorithmic notions of interpretability, fairness, accuracy, and robustness in medical applications of AI.

The lab is part of the Computational Health Informatics Program at Boston Children’s Hospital, affiliated with Harvard Medical School.

Recent Papers

Deep Time-to-Event Models for Intrapartum Fetal Monitoring
Guilherme S. Imai Aldeia, Helena Coggan, Yuting Yang, Lisa Levine, Jennifer A. McCoy, William G. La Cava (2026)
Preprint
pdf
A pre-train and fine-tune framework for adaptive boosting of pre-trained polygenic risk scores
Jie Hu, Raelynn Chen, Maxwell Salvatore, Olivia Wu, Okan Bilge Ozdemir, Yiwen Lu, Shawn N. Murphy, Elizabeth W. Karlson, Atlas Khan, Krzysztof Kiryluk, Iftikhar J. Kullo, Johanna L. Smith, Eimear E. Kenny, Yuan Luo, Zaldy S. Tan, William G. La Cava, Marylyn D. Ritchie, Yong Chen, Ruowang Li (2026)
Nature Communications
nature.com  |  pdf
A foundation-model approach to pediatric headache classification from rs-fMRI
Guilherme S. Imai Aldeia, Clara Moon, Julie Shulman, Navil Sethna, Allison Smith, Alyssa Lebel, William G. La Cava, Scott Holmes (2026)
Machine Learning for Healthcare Conference
arxiv.org  |  pdf  | In press

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