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Neil A. Tenenholtz
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2020 – today
- 2024
- [c13]Junhong Shen, Neil A. Tenenholtz, James Brian Hall, David Alvarez-Melis, Nicolò Fusi:
Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains. ICML 2024 - [c12]Ruiwen Ding, James Brian Hall, Neil A. Tenenholtz, Kristen Severson:
Improving Mitosis Detection on Histopathology Images Using Large Vision-Language Models. ISBI 2024: 1-5 - [i13]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, Atlas Haddadi Avval, Susan Sotardi, Neil A. Tenenholtz, Felipe Kitamura, Timothy Kline:
RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models. CoRR abs/2401.08847 (2024) - [i12]Junhong Shen, Neil A. Tenenholtz, James Brian Hall, David Alvarez-Melis, Nicolò Fusi:
Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains. CoRR abs/2402.05140 (2024) - [i11]Eric Zimmermann, Neil A. Tenenholtz, James Brian Hall, George Shaikovski, Michal Zelechowski, Adam Casson, Fausto Milletari, Julian Viret, Eugene Vorontsov, Siqi Liu, Kristen Severson:
Adapting Self-Supervised Learning for Computational Pathology. CoRR abs/2405.01688 (2024) - [i10]George Shaikovski, Adam Casson, Kristen Severson, Eric Zimmermann, Yi Kan Wang, Jeremy D. Kunz, Juan Retamero, Gerard Oakley, David S. Klimstra, Christopher Kanan, Matthew G. Hanna, Michal Zelechowski, Julian Viret, Neil A. Tenenholtz, James Brian Hall, Nicolò Fusi, Razik Yousfi, Peter Hamilton, William A. Moye, Eugene Vorontsov, Siqi Liu, Thomas J. Fuchs:
PRISM: A Multi-Modal Generative Foundation Model for Slide-Level Histopathology. CoRR abs/2405.10254 (2024) - [i9]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, Siqi Liu, Kristen Severson:
Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology. CoRR abs/2408.00738 (2024) - 2023
- [c11]Hammaad Adam, Fan Yin, Huibin Hu, Neil A. Tenenholtz, Lorin Crawford, Lester Mackey, Allison Koenecke:
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations. NeurIPS 2023 - [i8]Hammaad Adam, Fan Yin, Mary Hu, Neil A. Tenenholtz, Lorin Crawford, Lester Mackey, Allison Koenecke:
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations. CoRR abs/2306.11839 (2023) - [i7]Ruiwen Ding, James Brian Hall, Neil A. Tenenholtz, Kristen Severson:
Improving mitosis detection on histopathology images using large vision-language models. CoRR abs/2310.07176 (2023) - 2022
- [i6]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, Elad Walach, George Shih, Steve Langer:
Best Practices and Scoring System on Reviewing A.I. based Medical Imaging Papers: Part 1 Classification. CoRR abs/2202.01863 (2022) - 2021
- [c10]Mikhail Khodak, Neil A. Tenenholtz, Lester Mackey, Nicolò Fusi:
Initialization and Regularization of Factorized Neural Layers. ICLR 2021 - [i5]Mikhail Khodak, Neil A. Tenenholtz, Lester Mackey, Nicolò Fusi:
Initialization and Regularization of Factorized Neural Layers. CoRR abs/2105.01029 (2021) - 2020
- [j1]Romane Gauriau, Christopher P. Bridge, Lina Chen, Felipe Kitamura, Neil A. Tenenholtz, John E. Kirsch, Katherine P. Andriole, Mark H. Michalski, Bernardo C. Bizzo:
Using DICOM Metadata for Radiological Image Series Categorization: a Feasibility Study on Large Clinical Brain MRI Datasets. J. Digit. Imaging 33(3): 747-762 (2020)
2010 – 2019
- 2019
- [c9]Andriy Myronenko, Dong Yang, Varun Buch, Daguang Xu, Alvin Ihsani, Sean Doyle, Mark Michalski, Neil A. Tenenholtz, Holger Roth:
4D CNN for Semantic Segmentation of Cardiac Volumetric Sequences. STACOM@MICCAI 2019: 72-80 - [c8]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:
DeepAAA: Clinically Applicable and Generalizable Detection of Abdominal Aortic Aneurysm Using Deep Learning. MICCAI (2) 2019: 723-731 - [i4]Andriy Myronenko, Dong Yang, Varun Buch, Daguang Xu, Alvin Ihsani, Sean Doyle, Mark Michalski, Neil A. Tenenholtz, Holger Roth:
4D CNN for semantic segmentation of cardiac volumetric sequences. CoRR abs/1906.07295 (2019) - [i3]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:
DeepAAA: clinically applicable and generalizable detection of abdominal aortic aneurysm using deep learning. CoRR abs/1907.02567 (2019) - 2018
- [c7]Hoo-Chang Shin, Neil A. Tenenholtz, Jameson K. Rogers, Christopher G. Schwarz, Matthew L. Senjem, Jeffrey L. Gunter, Katherine P. Andriole, Mark Michalski:
Medical Image Synthesis for Data Augmentation and Anonymization Using Generative Adversarial Networks. SASHIMI@MICCAI 2018: 1-11 - [c6]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:
Detection and Delineation of Acute Cerebral Infarct on DWI Using Weakly Supervised Machine Learning. MICCAI (3) 2018: 81-88 - [c5]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, Marisa Welch, Caitlin Zellers, Neil A. Tenenholtz, Mark Michalski, Brian Wolpin, Katherine P. Andriole:
Fully-Automated Analysis of Body Composition from CT in Cancer Patients Using Convolutional Neural Networks. OR 2.0/CARE/CLIP/ISIC@MICCAI 2018: 204-213 - [i2]Hoo-Chang Shin, Neil A. Tenenholtz, Jameson K. Rogers, Christopher G. Schwarz, Matthew L. Senjem, Jeffrey L. Gunter, Katherine P. Andriole, Mark Michalski:
Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks. CoRR abs/1807.10225 (2018) - [i1]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, Marisa Welch, Caitlin Zellers, Neil A. Tenenholtz, Mark Michalski, Brian Wolpin, Katherine P. Andriole:
Fully-Automated Analysis of Body Composition from CT in Cancer Patients Using Convolutional Neural Networks. CoRR abs/1808.03844 (2018) - 2015
- [c4]Andrew Sutcliffe, Neil A. Tenenholtz, Joelle Pineau:
Missteps in Robot Social Navigation. AAAI Fall Symposia 2015: 134-136 - 2013
- [c3]Neil A. Tenenholtz, Peter E. Hammer, Assunta Fabozzo, Eric N. Feins, Pedro J. del Nido, Robert D. Howe:
Fast Simulation of Mitral Annuloplasty for Surgical Planning. FIMH 2013: 106-113 - 2011
- [c2]Neil A. Tenenholtz, Peter E. Hammer, Robert J. Schneider, Nikolay V. Vasilyev, Robert D. Howe:
On the design of an interactive, patient-specific surgical simulator for mitral valve repair. IROS 2011: 1327-1332 - [c1]Robert J. Schneider, Neil A. Tenenholtz, Douglas P. Perrin, Gerald R. Marx, Pedro J. del Nido, Robert D. Howe:
Patient-Specific Mitral Leaflet Segmentation from 4D Ultrasound. MICCAI (3) 2011: 520-527
Coauthor Index
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last updated on 2024-10-07 22:12 CEST by the dblp team
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