Federated Learning for the Classification of Tumor Infiltrating
Lymphocytes

Federated Learning for the Classification of Tumor Infiltrating Lymphocytes

30 March 2022

Rajarsi R. Gupta

Shahira Abousamra

Siddhesh P. Thakur

Spyridon Bakas

Papers citing "Federated Learning for the Classification of Tumor Infiltrating Lymphocytes"

7 / 7 papers shown

Title
Multi-task Federated Learning for Heterogeneous Pancreas Segmentation Chen Shen Pochuan Wang H. Roth Dong Yang Daguang Xu ... C. Fuh Po-Ting Chen Kao-Lang Liu W. Liao K. Mori FedML 57 41 0 19 Aug 2021
The Future of Digital Health with Federated Learning Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 218 1,746 0 18 Mar 2020
Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types Shahira Abousamra L. Hou Rajarsi R. Gupta Chao Chen Dimitris Samaras Tahsin M. Kurc R. Batiste Tianhao Zhao S. Kenneth Joel H. Saltz 14 10 0 09 Jul 2019
Multi-Institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation Micah J. Sheller G. A. Reina Brandon Edwards Jason Martin Spyridon Bakas FedML 36 458 0 10 Oct 2018
Deep Learning using Rectified Linear Units (ReLU) Abien Fred Agarap 45 3,195 0 22 Mar 2018
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 169 17,235 0 17 Feb 2016
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 367 99,991 0 04 Sep 2014