On the design of an interactive, patient-specific surgical simulator for mitral valve repair. - Neil A. Tenenholtz; Peter E. Hammer; Robert J. Schneider; Nikolay V. Vasilyev; Robert D. Howe (IROS, 2011)

Patient-Specific Mitral Leaflet Segmentation from 4D Ultrasound. - Robert J. Schneider; Neil A. Tenenholtz; Douglas P. Perrin; Gerald R. Marx; Pedro J. del Nido; Robert D. Howe (MICCAI (3), 2011)

Fast Simulation of Mitral Annuloplasty for Surgical Planning. - Neil A. Tenenholtz; Peter E. Hammer; Assunta Fabozzo; Eric N. Feins; Pedro J. del Nido; Robert D. Howe (FIMH, 2013)

Missteps in Robot Social Navigation. - Andrew Sutcliffe; Neil A. Tenenholtz; Joelle Pineau (AAAI Fall Symposia, 2015)

Fully-Automated Analysis of Body Composition from CT in Cancer Patients Using Convolutional Neural Networks. - Christopher P. Bridge; Michael H. Rosenthal; Bradley Wright; Gopal Kotecha; Florian J. Fintelmann; Fabian M. Troschel; Nityanand Miskin; Khanant Desai; William Wrobel; Ana Babic; Natalia Khalaf; Lauren Brais; et al. (OR 2.0/CARE/CLIP/ISIC@MICCAI, 2018)

Detection and Delineation of Acute Cerebral Infarct on DWI Using Weakly Supervised Machine Learning. - Stefano Pedemonte; Bernardo Bizzo; Stuart R. Pomerantz; Neil A. Tenenholtz; Bradley Wright; Mark Walters; Sean Doyle; Adam McCarthy; Renata Rocha De Almeida; Katherine P. Andriole; Mark Michalski; R. Gilberto González (MICCAI (3), 2018)

Medical Image Synthesis for Data Augmentation and Anonymization Using Generative Adversarial Networks. - Hoo-Chang Shin; Neil A. Tenenholtz; Jameson K. Rogers; Christopher G. Schwarz; Matthew L. Senjem; Jeffrey L. Gunter; Katherine P. Andriole; Mark Michalski (SASHIMI@MICCAI, 2018)

DeepAAA: Clinically Applicable and Generalizable Detection of Abdominal Aortic Aneurysm Using Deep Learning. - Jen-Tang Lu; Rupert Brooks; Stefan Hahn; Jin Chen; Varun Buch; Gopal Kotecha; Katherine P. Andriole; Brian B. Ghoshhajra; Joel Pinto; Paul Vozila; Mark Michalski; Neil A. Tenenholtz (MICCAI (2), 2019)

4D CNN for Semantic Segmentation of Cardiac Volumetric Sequences. - Andriy Myronenko; Dong Yang 005; Varun Buch; Daguang Xu; Alvin Ihsani; Sean Doyle; Mark Michalski; Neil A. Tenenholtz; Holger Roth (STACOM@MICCAI, 2019)

Using DICOM Metadata for Radiological Image Series Categorization: a Feasibility Study on Large Clinical Brain MRI Datasets. - Romane Gauriau; Christopher P. Bridge; Lina Chen; Felipe Kitamura; Neil A. Tenenholtz; John E. Kirsch; Katherine P. Andriole; Mark H. Michalski; Bernardo C. Bizzo (J. Digit. Imaging, 2020)

Initialization and Regularization of Factorized Neural Layers. - Mikhail Khodak; Neil A. Tenenholtz; Lester Mackey; Nicolò Fusi (ICLR, 2021)

Best Practices and Scoring System on Reviewing A.I. based Medical Imaging Papers: Part 1 Classification. - Timothy L. Kline; Felipe Kitamura; Ian Pan; Amine M. Korchi; Neil A. Tenenholtz; Linda Moy; Judy Wawira Gichoya; Igor Santos; Steven Blumer; Misha Ysabel Hwang; Kim-Ann Git; Abishek Shroff; et al. (CoRR, 2022)

Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations. - Hammaad Adam; Fan Yin; Huibin Hu; Neil A. Tenenholtz; Lorin Crawford; Lester Mackey; Allison Koenecke (NeurIPS, 2023)

Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations. - Hammaad Adam; Fan Yin; Mary Hu; Neil A. Tenenholtz; Lorin Crawford; Lester Mackey; Allison Koenecke (CoRR, 2023)

Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains. - Junhong Shen; Neil A. Tenenholtz; James Brian Hall; David Alvarez-Melis; Nicolò Fusi (ICML, 2024)

Improving Mitosis Detection on Histopathology Images Using Large Vision-Language Models. - Ruiwen Ding; James Brian Hall; Neil A. Tenenholtz; Kristen Severson 001 (ISBI, 2024)

RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models. - Farhad Maleki; Linda Moy; Reza Forghani; Tapotosh Ghosh; Katie L. Ovens; Steve Langer; Pouria Rouzrokh; Bardia Khosravi; Ali Ganjizadeh; Daniel I. Warren; Roxana Daneshjou; Mana Moassefi; et al. (CoRR, 2024)

Adapting Self-Supervised Learning for Computational Pathology. - Eric Zimmermann; Neil A. Tenenholtz; James Brian Hall; George Shaikovski; Michal Zelechowski; Adam Casson; Fausto Milletari; Julian Viret; Eugene Vorontsov; Siqi Liu; Kristen Severson 001 (CoRR, 2024)

PRISM: A Multi-Modal Generative Foundation Model for Slide-Level Histopathology. - George Shaikovski; Adam Casson; Kristen Severson 001; Eric Zimmermann; Yi Kan Wang; Jeremy D. Kunz; Juan Retamero; Gerard Oakley; David S. Klimstra; Christopher Kanan; Matthew G. Hanna; Michal Zelechowski; et al. (CoRR, 2024)

Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology. - Eric Zimmermann; Eugene Vorontsov; Julian Viret; Adam Casson; Michal Zelechowski; George Shaikovski; Neil A. Tenenholtz; James Brian Hall; David S. Klimstra; Razik Yousfi; Thomas J. Fuchs; Nicoló Fusi; et al. (CoRR, 2024)

Causal integration of chemical structures improves representations of microscopy images for morphological profiling. - Yemin Yu; Neil A. Tenenholtz; Lester Mackey; Ying Wei; David Alvarez-Melis; Ava P. Amini; Alex X. Lu (CoRR, 2025)

PRISM2: Unlocking Multi-Modal General Pathology AI with Clinical Dialogue. - George Shaikovski; Eugene Vorontsov; Adam Casson; Julian Viret; Eric Zimmermann; Neil A. Tenenholtz; Yi Kan Wang; Jan Bernhard; Ran A. Godrich; Juan Retamero; Razik Yousfi; Nicolò Fusi; et al. (CoRR, 2025)