Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Neil Tenenholtz

Neil Tenenholtz

Best Practices and Scoring System on Reviewing A.I. based Medical Imaging Papers: Part 1 Classification


Feb 03, 2022
Timothy L. Kline, Felipe Kitamura, Ian Pan, Amine M. Korchi, Neil Tenenholtz, Linda Moy, Judy Wawira Gichoya, Igor Santos, Steven Blumer, Misha Ysabel Hwang, Kim-Ann Git, Abishek Shroff, Elad Walach, George Shih, Steve Langer

Figure 1 for Best Practices and Scoring System on Reviewing A.I. based Medical Imaging Papers: Part 1 Classification
Figure 2 for Best Practices and Scoring System on Reviewing A.I. based Medical Imaging Papers: Part 1 Classification
Figure 3 for Best Practices and Scoring System on Reviewing A.I. based Medical Imaging Papers: Part 1 Classification

  Access Paper or Ask Questions

Initialization and Regularization of Factorized Neural Layers


May 03, 2021
Mikhail Khodak, Neil Tenenholtz, Lester Mackey, Nicolò Fusi

Figure 1 for Initialization and Regularization of Factorized Neural Layers
Figure 2 for Initialization and Regularization of Factorized Neural Layers
Figure 3 for Initialization and Regularization of Factorized Neural Layers
Figure 4 for Initialization and Regularization of Factorized Neural Layers
* ICLR 2021 Camera-Ready 
  Access Paper or Ask Questions

4D CNN for semantic segmentation of cardiac volumetric sequences


Jun 17, 2019
Andriy Myronenko, Dong Yang, Varun Buch, Daguang Xu, Alvin Ihsani, Sean Doyle, Mark Michalski, Neil Tenenholtz, Holger Roth

Figure 1 for 4D CNN for semantic segmentation of cardiac volumetric sequences
Figure 2 for 4D CNN for semantic segmentation of cardiac volumetric sequences
Figure 3 for 4D CNN for semantic segmentation of cardiac volumetric sequences
Figure 4 for 4D CNN for semantic segmentation of cardiac volumetric sequences

  Access Paper or Ask Questions

Fully-Automated Analysis of Body Composition from CT in Cancer Patients Using Convolutional Neural Networks


Aug 11, 2018
Christopher P. Bridge, Michael Rosenthal, Bradley Wright, Gopal Kotecha, Florian Fintelmann, Fabian Troschel, Nityanand Miskin, Khanant Desai, William Wrobel, Ana Babic, Natalia Khalaf, Lauren Brais, Marisa Welch, Caitlin Zellers, Neil Tenenholtz, Mark Michalski, Brian Wolpin, Katherine Andriole

Figure 1 for Fully-Automated Analysis of Body Composition from CT in Cancer Patients Using Convolutional Neural Networks
Figure 2 for Fully-Automated Analysis of Body Composition from CT in Cancer Patients Using Convolutional Neural Networks
Figure 3 for Fully-Automated Analysis of Body Composition from CT in Cancer Patients Using Convolutional Neural Networks
Figure 4 for Fully-Automated Analysis of Body Composition from CT in Cancer Patients Using Convolutional Neural Networks

  Access Paper or Ask Questions