Journal Article

Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence.

Liang H; Tsui BY; Ni H; Valentim CCS; Baxter SL; Liu G; Cai W; Kermany DS; Sun X; Chen J; He L; Zhu J; Tian P; Shao H; Zheng L; Hou R; Hewett S; Li G; Liang P; Zang X; Zhang Z; Pan L; Cai H; Ling R; Li S; Cui Y; Tang S; Ye H; Huang X; He W; Liang W; Zhang Q; Jiang J; Yu W; Gao J; Ou W; Deng Y; Hou Q; Wang B; Yao C; Liang Y; Zhang S; Duan Y; Zhang R; Gibson S; Zhang CL; Li O; Zhang ED; Karin G; Nguyen N; Wu X; Wen C; Xu J; Xu W; Wang B; Wang W; Li J; Pizzato B; Bao C; Xiang D; He W; He S; Zhou Y; Haw W; Goldbaum M; Tremoulet A; Hsu CN; Carter H; Zhu L; Zhang K; Xia H.
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Artificial intelligence may have the potential to improve patient safety by enhancing diagnostic capability. In this study, researchers applied machine learning techniques to a large amount of pediatric electronic health record data and found that their model was able to achieve diagnostic accuracy analogous to that of skilled pediatricians.