Using Interpretable Machine Learning to Predict Maternal and Fetal Outcomes. - Tomas M. Bosschieter; Zifei Xu; Hui Lan; Benjamin J. Lengerich; Harsha Nori; Kristin Sitcov; Vivienne Souter; Rich Caruana (CoRR, 2022)

The Missing Indicator Method: From Low to High Dimensions. - Mike Van Ness; Tomas M. Bosschieter; Roberto Halpin-Gregorio; Madeleine Udell (KDD, 2023)

Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Model. - Wei Peng 009; Ehsan Adeli 001; Tomas M. Bosschieter; Sanghyun Park 004; Qingyu Zhao; Kilian M. Pohl (MICCAI (8), 2023)

Interpretable Survival Analysis for Heart Failure Risk Prediction. - Mike Van Ness; Tomas M. Bosschieter; Natasha Din; Andrew Ambrosy; Alexander Sandhu; Madeleine Udell (ML4H@NeurIPS, 2023)

Metadata-Conditioned Generative Models to Synthesize Anatomically-Plausible 3D Brain MRIs. - Wei Peng 009; Tomas M. Bosschieter; Jiahong Ouyang; Robert Paul; Ehsan Adeli 001; Qingyu Zhao; Kilian M. Pohl (CoRR, 2023)

Latent 3D Brain MRI Counterfactual. - Wei Peng 009; Tian Xia; Fabio De Sousa Ribeiro; Tomas M. Bosschieter; Ehsan Adeli-Mosabbeb; Qingyu Zhao; Ben Glocker; Kilian M. Pohl (CoRR, 2024)

Metadata-conditioned generative models to synthesize anatomically-plausible 3D brain MRIs. - Wei Peng 009; Tomas M. Bosschieter; Jiahong Ouyang; Robert Paul; Edith V. Sullivan; Adolf Pfefferbaum; Ehsan Adeli 001; Qingyu Zhao; Kilian M. Pohl (Medical Image Anal., 2024)

Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes. - Tomas M. Bosschieter; Zifei Xu; Hui Lan; Benjamin J. Lengerich; Harsha Nori; Ian S. Painter; Vivienne Souter; Rich Caruana (J. Heal. Informatics Res., 2024)

The Most Important Features in Generalized Additive Models Might Be Groups of Features. - Tomas M. Bosschieter; Luis Franca; Jessica Wolk; Yiyuan Wu; Bella Mehta; Joseph Dehoney; Orsolya Kiss; Fiona C. Baker; Qingyu Zhao; Rich Caruana; Kilian M. Pohl (CoRR, 2025)