Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence

Autor: Huimin Cai, Yugui Zhou, Zhiqi Zhang, Hua Shao, Charlotte Zhang, Xin Sun, Qiaozhen Hou, Cuichan Yao, Xiaokang Wu, Shusheng Tang, Jie Zhu, Brian Tsui, Yaou Duan, Yongwang Cui, Edward Zhang, Gabriel Karin, Shuhua Li, Huimin Xia, Waner He, Rui Hou, Bei Wang, Wanxing Ou, Jianmin Jiang, Daoman Xiang, Sally L. Baxter, Sierra Hewett, Yingmin Deng, Wenqing Liang, Winston Wang, Bianca Pizzato, Weldon W Haw, Caroline Bao, Kang Zhang, Runze Zhang, Hao Ni, Long Zhu, Liya He, Xuan Zang, Ping Liang, Chun-Nan Hsu, Wanting He, Daniel S. Kermany, Cindy Wen, Jie Xu, Qing Zhang, Gen Li, Nathan Nguyen, Liyan Pan, Suiqin He, Bochu Wang, Rujuan Ling, Pin Tian, Yan Liang, Huiying Liang, Jianqun Gao, Adriana H. Tremoulet, Jiancong Chen, Guangjian Liu, Oulan Li, Shu Zhang, Michael H. Goldbaum, Carolina C. S. Valentim, Hong Ye, Wei Yu, Jing Li, Wenqin Xu, Wenjia Cai, Hannah Carter, Sarah Gibson, Xiaoyan Huang, Lianghong Zheng

Publikováno v: Nature medicine. 25(3)

Artificial intelligence (AI)-based methods have emerged as powerful tools to transform medical care. Although machine learning classifiers (MLCs) have already demonstrated strong performance in image-based diagnoses, analysis of diverse and massive e

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98526d3e76d7c0f6cc38677f2b7a8488
https://pubmed.ncbi.nlm.nih.gov/30742121