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Aoxiao Zhong
Researcher at Harvard University
Publications - 18
Citations - 3164
Aoxiao Zhong is an academic researcher from Harvard University. The author has contributed to research in topics: Deep learning & Computer science. The author has an hindex of 6, co-authored 14 publications receiving 1896 citations. Previous affiliations of Aoxiao Zhong include Zhejiang University & Peking University.
Papers
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Journal ArticleDOI
Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.
Babak Ehteshami Bejnordi,Mitko Veta,Paul J. van Diest,Bram van Ginneken,Nico Karssemeijer,Geert Litjens,Jeroen van der Laak,Meyke Hermsen,Quirine F. Manson,Maschenka Balkenhol,Oscar Geessink,N. Stathonikos,Marcory C. R. F. van Dijk,Peter Bult,Francisco Beca,Andrew H. Beck,Dayong Wang,Aditya Khosla,Rishab Gargeya,Humayun Irshad,Aoxiao Zhong,Qi Dou,Qi Dou,Quanzheng Li,Hao Chen,Huangjing Lin,Pheng-Ann Heng,Christian Haß,Elia Bruni,Quincy Wong,Ugur Halici,Mustafa Umit Oner,Rengul Cetin-Atalay,Matt Berseth,Vitali Khvatkov,Alexei Vylegzhanin,Oren Kraus,Muhammad Shaban,Nasir M. Rajpoot,Nasir M. Rajpoot,Ruqayya Awan,Korsuk Sirinukunwattana,Talha Qaiser,Yee-Wah Tsang,David Tellez,Jonas Annuscheit,Peter Hufnagl,Mira Valkonen,Kimmo Kartasalo,Kimmo Kartasalo,Leena Latonen,Pekka Ruusuvuori,Pekka Ruusuvuori,Kaisa Liimatainen,Shadi Albarqouni,Bharti Mungal,Ami George,Stefanie Demirci,Nassir Navab,Seiryo Watanabe,Shigeto Seno,Yoichi Takenaka,Hideo Matsuda,Hady Ahmady Phoulady,Vassili Kovalev,A. Kalinovsky,Vitali Liauchuk,Gloria Bueno,M. Milagro Fernández-Carrobles,Ismael Serrano,Oscar Deniz,Daniel Racoceanu,Daniel Racoceanu,Rui Venâncio +73 more
TL;DR: In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints.
Journal ArticleDOI
From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge
Péter Bándi,Oscar Geessink,Quirine F. Manson,Marcory C. R. F. van Dijk,Maschenka Balkenhol,Meyke Hermsen,Babak Ehteshami Bejnordi,Byungjae Lee,Kyunghyun Paeng,Aoxiao Zhong,Quanzheng Li,Farhad Ghazvinian Zanjani,Svitlana Zinger,Keisuke Fukuta,Daisuke Komura,Vlado Ovtcharov,Shenghua Cheng,Shaoqun Zeng,Jeppe Thagaard,Anders Bjorholm Dahl,Huangjing Lin,Hao Chen,Ludwig Jacobsson,Martin Hedlund,Melih cetin,Eren Halici,Hunter Jackson,Richard J. Chen,Fabian Both,Jörg Franke,Heidi V.N. Küsters-Vandevelde,Willem Vreuls,Peter Bult,Bram van Ginneken,Jeroen van der Laak,Geert Litjens +35 more
TL;DR: It is shown that simple combinations of the top algorithms result in higher kappa metric values than any algorithm individually, with 0.93 for the best combination.
Proceedings Article
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
TL;DR: In this paper, a linear multi-step architecture (LM-architecture) is proposed for deep neural networks, which is inspired by the linear mult-step method solving ordinary differential equations.
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 Content
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
TL;DR: In this paper, a linear multi-step architecture (LM-architecture) is proposed for deep neural networks, which is inspired by the linear mult-step method solving ordinary differential equations.