Dynamic prediction of hypoxemia risk at different time points based on preoperative and intraoperative features: machine learning applications in outpatients undergoing esophagogastroduodenoscopy

Zhaojing Fanga Department of Anesthesiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, P.R. ChinaView further author information

Daizun Zoub School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, P.R. China;c Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, P.R. ChinaView further author information

Weigen Xiongb School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, P.R. China;c Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, P.R. ChinaView further author information

Hongguang Baoa Department of Anesthesiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, P.R. ChinaView further author information

Xiuxiu Zhaoa Department of Anesthesiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, P.R. ChinaView further author information

Chen Chenc Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, P.R. China;d Department of Pharmacy, Nanjing First Hospital, China Pharmaceutical University, Nanjing, P.R. ChinaView further author information

Yanna Sia Department of Anesthesiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, P.R. ChinaCorrespondence[email protected]
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Jianjun Zouc Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, P.R. China;d Department of Pharmacy, Nanjing First Hospital, China Pharmaceutical University, Nanjing, P.R. ChinaCorrespondence[email protected]
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Dynamic prediction of hypoxemia risk at different time points based on preoperative and intraoperative features: machine learning applications in outpatients undergoing esophagogastroduodenoscopy

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Dynamic prediction of hypoxemia risk at different time points based on preoperative and intraoperative features: machine learning applications in outpatients undergoing esophagogastroduodenoscopy

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