A
Abood Quraini
Researcher at Nvidia
Publications - 4
Citations - 194
Abood Quraini is an academic researcher from Nvidia. The author has contributed to research in topics: Computer science & Health care. The author has an hindex of 2, co-authored 2 publications receiving 8 citations.
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Journal ArticleDOI
Federated learning for predicting clinical outcomes in patients with COVID-19.
Ittai Dayan,Holger R. Roth,Aoxiao Zhong,Ahmed Harouni,Amilcare Gentili,Anas Z. Abidin,Andrew Liu,Anthony Costa,Bradford J. Wood,Chien-Sung Tsai,Chih-Hung Wang,Chun-Nan Hsu,C. K. Lee,Peiying Ruan,Daguang Xu,Dufan Wu,Eddie Huang,Felipe Kitamura,Griffin Lacey,Gustavo César de Antônio Corradi,Gustavo Nino,Hao-Hsin Shin,Hirofumi Obinata,Hui Ren,Jason C. Crane,Jesse Tetreault,Jiahui Guan,John Garrett,Joshua D. Kaggie,Jung Gil Park,Keith J. Dreyer,Krishna Juluru,Kristopher Kersten,Marcio Aloisio Bezerra Cavalcanti Rockenbach,Marius George Linguraru,Marius George Linguraru,Masoom A. Haider,Masoom A. Haider,Meena AbdelMaseeh,Nicola Rieke,Pablo F. Damasceno,Pedro Mário Cruz e Silva,Pochuan Wang,Sheng Xu,Shuichi Kawano,Sira Sriswasdi,Soo-Young Park,Thomas M. Grist,Varun Buch,Watsamon Jantarabenjakul,Watsamon Jantarabenjakul,Weichung Wang,Won Young Tak,Xiang Li,Xihong Lin,Young Joon Kwon,Abood Quraini,Andrew Feng,Andrew N. Priest,Baris Turkbey,Benjamin S. Glicksberg,Bernardo Bizzo,Byung Seok Kim,Carlos Tor-Díez,Chia-Cheng Lee,Chia-Jung Hsu,Chin Lin,Chiu-Ling Lai,Christopher P. Hess,Colin B. Compas,Deepeksha Bhatia,Eric K. Oermann,Evan Leibovitz,Hisashi Sasaki,Hitoshi Mori,Isaac Yang,Jae Ho Sohn,Krishna Nand Keshava Murthy,Li-Chen Fu,Matheus Ribeiro Furtado de Mendonça,Mike Fralick,Min Kyu Kang,Mohammad Adil,Natalie Gangai,Peerapon Vateekul,Pierre Elnajjar,Sarah E Hickman,Sharmila Majumdar,Shelley McLeod,Sheridan Reed,Stefan Gräf,Stephanie Harmon,Tatsuya Kodama,Thanyawee Puthanakit,Thanyawee Puthanakit,Tony Mazzulli,Tony Mazzulli,Vitor Lavor,Yothin Rakvongthai,Yu Rim Lee,Yuhong Wen,Fiona J. Gilbert,Mona Flores,Quanzheng Li +103 more
TL;DR: In this article, the authors used federated learning to predict future oxygen requirements of symptomatic patients with COVID-19 using inputs of vital signs, laboratory data and chest X-rays.
Posted ContentDOI
Federated Learning used for predicting outcomes in SARS-COV-2 patients
Mona Flores,Ittai Dayan,Holger R. Roth,Aoxiao Zhong,Ahmed Harouni,Amilcare Gentili,Anas Z. Abidin,Andrew Liu,Anthony Costa,Bradford J. Wood,Chien-Sung Tsai,Chih-Hung Wang,Chun-Nan Hsu,C. K. Lee,Colleen Ruan,Daguang Xu,Dufan Wu,Eddie Huang,Felipe Kitamura,Griffin Lacey,Gustavo César de Antônio Corradi,Hao-Hsin Shin,Hirofumi Obinata,Hui Ren,Jason C. Crane,Jesse Tetreault,Jiahui Guan,John Garrett,Jung Gil Park,Keith J. Dreyer,Krishna Juluru,Kristopher Kersten,Marcio Aloisio Bezerra Cavalcanti Rockenbach,Marius George Linguraru,Masoom A. Haider,Meena Abdelmaseeh,Nicola Rieke,Pablo F. Damasceno,Pedro Mário Cruz e Silva,Pochuan Wang,Sheng Xu,Shuichi Kawano,Sira Sriswa,Soo-Young Park,Thomas M. Grist,Varun Buch,Watsamon Jantarabenjakul,Weichung Wang,Won Young Tak,Xiang Li,Xihong Lin,Fred Kwon,Fiona J. Gilbert,J. D. Kaggie,Quanzheng Li,Abood Quraini,Andrew Feng,Andrew N. Priest,Baris Turkbey,Benjamin S. Glicksberg,Bernardo Bizzo,Byung Seok Kim,Carlos Tor-Díez,Chia-Cheng Lee,Chia-Jung Hsu,Chin Lin,Chiu-Ling Lai,Christopher P. Hess,Colin B. Compas,Deepi Bhatia,Eric K. Oermann,Evan Leibovitz,Hisashi Sasaki,Hitoshi Mori,Isaac Yang,Jae Ho Sohn,Krishna Nand Keshava Murthy,Li-Chen Fu,Matheus Ribeiro Furtado de Mendonça,Mike Fralick,Min Kyu Kang,Mohammad Adil,Natalie Gangai,Peerapon Vateekul,Pierre Elnajjar,Sarah E Hickman,Sharmila Majumdar,Shelley McLeod,Sheridan Reed,Stefan Gräf,Stephanie Harmon,Tatsuya Kodama,Thanyawee Puthanakit,Tony Mazzulli,Vitor de Lima Lavor,Yothin Rakvongthai,Yu Rim Lee,Yuhong Wen +97 more
TL;DR: In this paper, the authors used federated learning to predict future oxygen requirements of infected patients using inputs of vital signs, laboratory data, and chest x-rays, constituting the "EXAM" (EMR CXR AI Model) model.
Journal ArticleDOI
NVIDIA FLARE: Federated Learning from Simulation to Real-World
Holger R. Roth,Yan Cheng,Yuhong Wen,Isaac Yang,Ziyue Xu,Yuan Ting Hsieh,Kristopher Kersten,Ahmed Harouni,Can Zhao,K. Lu,Zhihong Zhang,Wenqi Li,Andriy Myronenko,Dong Yang,Sean Bin Yang,Nicola Rieke,Abood Quraini,Chester G. Chen,Daguang Xu,Nic Ma,Prerna Dogra,Mona Flores,Andrew Feng +22 more
TL;DR: The key design principles of FLARE are introduced and some use cases are illustrated with customizable FL workflows that implement different privacy-preserving algorithms.
Book ChapterDOI
DeepEdit: Deep Editable Learning for Interactive Segmentation of 3D Medical Images
Andres Diaz-Pinto,Pritesh Mehta,Sachidanand Alle,Muhammad Hamza Asad,Richard Brown,Vishwesh Nath,Alvin Ihsani,Michela Antonelli,Daniel Palkovics,Csaba Pinter,Ron N. Alkalay,Steve Pieper,Holger R. Roth,Daguang Xu,Prerna Dogra,Tom Vercauteren,Andrew Feng,Abood Quraini,Sebastien Ourselin,M. Jorge Cardoso +19 more
TL;DR: DeepEdit as mentioned in this paper combines the power of two methods: a non-interactive (i.e. automatic segmentation using nnU-Net, UNET or UNETR) and an interactive segmentation method (e.g. DeepGrow), into a single deep learning model.