Tomas M. Bosschieter

According to our database, Tomas M. Bosschieter authored at least 9 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

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, June, 2025

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., March, 2024

Metadata-conditioned generative models to synthesize anatomically-plausible 3D brain MRIs.

Wei Peng, Tomas M. Bosschieter, Jiahong Ouyang, Robert Paul, Edith V. Sullivan, Adolf Pfefferbaum, Ehsan Adeli, Qingyu Zhao, Kilian M. Pohl

Medical Image Anal., 2024

Latent 3D Brain MRI Counterfactual.

Wei Peng, Tian Xia, Fabio De Sousa Ribeiro, Tomas M. Bosschieter, Ehsan Adeli-Mosabbeb, Qingyu Zhao, Ben Glocker, Kilian M. Pohl

CoRR, 2024

2023

Metadata-Conditioned Generative Models to Synthesize Anatomically-Plausible 3D Brain MRIs.

Wei Peng, Tomas M. Bosschieter, Jiahong Ouyang, Robert Paul, Ehsan Adeli, Qingyu Zhao, Kilian M. Pohl

CoRR, 2023

Interpretable Survival Analysis for Heart Failure Risk Prediction.

Mike Van Ness, Tomas M. Bosschieter, Natasha Din, Andrew Ambrosy, Alexander Sandhu, Madeleine Udell

Proceedings of the Machine Learning for Health, 2023

Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Model.

Wei Peng, Ehsan Adeli, Tomas M. Bosschieter, Sanghyun Park, Qingyu Zhao, Kilian M. Pohl

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

The Missing Indicator Method: From Low to High Dimensions.

Mike Van Ness, Tomas M. Bosschieter, Roberto Halpin-Gregorio, Madeleine Udell

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022

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