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Tomas Bosschieter
Tomas Bosschieter
Verified email at stanford.edu
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Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Model
W Peng, E Adeli, T Bosschieter, SH Park, Q Zhao, KM Pohl
International Conference on Medical Image Computing and Computer-Assisted …, 2023
25*2023
Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes
TM Bosschieter, Z Xu, H Lan, BJ Lengerich, H Nori, I Painter, V Souter, ...
Journal of Healthcare Informatics Research 8 (1), 65-87, 2024
8*2024
The missing indicator method: From low to high dimensions
M Van Ness, TM Bosschieter, R Halpin-Gregorio, M Udell
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
52023
Understanding risk factors for shoulder dystocia using interpretable machine learning
H Lan, TM Bosschieter, Z Xu, B Lengerich, H Nori, K Sitcov, I Painter, ...
American Journal of Obstetrics & Gynecology 228 (1), S753, 2023
22023
Interpretable survival analysis for heart failure risk prediction
M Van Ness, T Bosschieter, N Din, A Ambrosy, A Sandhu, M Udell
Machine Learning for Health (ML4H), 574-593, 2023
12023
Metadata-Conditioned Generative Models to Synthesize Anatomically-Plausible 3D Brain MRIs
W Peng, T Bosschieter, J Ouyang, R Paul, E Adeli, Q Zhao, KM Pohl
arXiv preprint arXiv:2310.04630, 2023
12023
Unique insights into risk factors for antepartum stillbirth using explainable AI
TM Bosschieter, H Lan, Z Xu, B Lengerich, H Nori, K Sitcov, I Painter, ...
American Journal of Obstetrics & Gynecology 228 (1), S403-S404, 2023
12023
Predicting severe maternal morbidity at admission for delivery using intelligible machine learning
Z Xu, TM Bosschieter, H Lan, B Lengerich, H Nori, K Sitcov, I Painter, ...
American Journal of Obstetrics & Gynecology 228 (1), S404-S405, 2023
12023
Preterm preeclampsia prediction using intelligible machine learning
TM Bosschieter, Z Xu, H Lan, B Lengerich, H Nori, K Sitcov, I Painter, ...
American Journal of Obstetrics & Gynecology 228 (1), S409, 2023
12023
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