Exploring the assessment of post-cardiac valve surgery pulmonary complication risks through the integration of wearable continuous physiological and clinical data

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Veröffentlicht in:	BMC Medical Informatics and Decision Making vol. 25 (2025), p. 1
1. Verfasser:	Li, Lixuan
Weitere Verfasser:	Hu, Yuekong, Yang, Zhicheng, Luo, Zeruxin, Wang, Jiachen, Wang, Wenqing, Liu, Xiaoli, Wang, Yuqiang, Fan, Yong, Yu, Pengming, Zhang, Zhengbo
Veröffentlicht:	Springer Nature B.V.
Schlagworte:	Sichuan University China Physiology Medical records Datasets Performance evaluation Regression analysis Wearable technology Risk assessment Machine learning Mortality Surgery Data analysis Postoperative Complications Hospitals Sleep apnea Optimization Morbidity Impact analysis Algorithms Information processing Patients Respiratory failure Decision making Heart Regression models Vital signs Heart valves Abdomen Economic impact Consent Electronic health records Pneumonia Artificial intelligence Heart surgery Cardiovascular diseases Wearable computers Data collection Medical prognosis
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