| An explainable artificial intelligence predictor for early detection of sepsis M Yang, C Liu, X Wang, Y Li, H Gao, X Liu, J Li Critical care medicine 48 (11), e1091-e1096, 2020 | 73 | 2020 |
| Wearable ECG: History, Key Technologies and Future Challenges C Liu, M Yang, J Di, Y Xing, Y Li, J Li Chinese Journal of Biomedical Engineering 38 (6), 641-652, 2019 | 33 | 2019 |
| Entropy Analysis of Heart Rate Variability in Different Sleep Stages Chang Yan, Peng Li, Meicheng Yang, Yang Li, Jianqing Li, Hongxing Zhang ... Entropy 24 (3), 379, 2022 | 26 | 2022 |
| Early Prediction of Sepsis Using Multi-Feature Fusion Based XGBoost Learning and Bayesian Optimization M Yang, X Wang, H Gao, Y Li, X Liu, J Li, C Liu 2019 Computing in Cardiology Conference (CinC) 46, 1-4, 2019 | 17 | 2019 |
| Identification of indications for albumin administration in septic patients with liver cirrhosis W Hu, H Chen, C Ma, Q Sun, M Yang, H Wang, Q Peng, J Wang, C Zhang, ... Critical Care 27 (1), 300, 2023 | 16 | 2023 |
| Database-based machine learning in sepsis deserves attention W Hu, M Yang, H Chen Intensive Care Medicine 49 (2), 262-263, 2023 | 8 | 2023 |
| Decision Tree-based Model for Signal Quality Scanning in Wearable ECG C Ma, Z Wang, M Yang, J Li, C Liu 2022 Computing in Cardiology Conference (CinC) 49, 1-4, 2022 | 3 | 2022 |
| Continuous prediction and clinical alarm management of late-onset sepsis in preterm infants using vital signs from a patient monitor M Yang, Z Peng, C van Pul, P Andriessen, K Dong, D Silvertand, J Li, ... Computer Methods and Programs in Biomedicine 255, 108335, 2024 | 2 | 2024 |
| An atrial fibrillation detection strategy in dynamic ECGs with significant individual differences C Ma, X Long, W Sheng, R Vullings, M Yang, L Zhao, RM Aarts, J Li, C Liu IEEE Transactions on Instrumentation and Measurement, 2023 | 2 | 2023 |
| A pretrain-finetune approach for improving model generalizability in outcome prediction of acute respiratory distress syndrome patients S Lin, M Yang, C Liu, Z Wang, X Long International Journal of Medical Informatics 186, 105397, 2024 | 1 | 2024 |
| Development and validation of a deep interpretable network for continuous acute kidney injury prediction in critically ill patients M Yang, S Liu, T Hao, C Ma, H Chen, Y Li, C Wu, J Xie, H Qiu, J Li, ... Artificial Intelligence in Medicine 149, 102785, 2024 | 1 | 2024 |
| Enhancing Patient Selection in Sepsis Clinical Trials Design Through an AI Enrichment Strategy: Algorithm Development and Validation M Yang, J Zhuang, W Hu, J Li, Y Wang, Z Zhang, C Liu, H Chen Journal of Medical Internet Research 26, e54621, 2024 | | 2024 |
| Interpretable XGBoost-SHAP Model for Arrhythmic Heartbeat Classification R Xiao, M Yang, C Ma, L Zhao, J Li, C Liu Computing 51, 1, 2024 | | 2024 |
| Development and validation of an interpretable conformal predictor to predict sepsis mortality risk: Retrospective cohort study M Yang, H Chen, W Wu, M Mischi, C Shan, J Li, X Long, C Liu Journal of Medical Internet Research 26, e50369, 2024 | | 2024 |
| An Explainable AI Predictor to Improve Clinical Prognosis for Acute Respiratory Distress Syndrome S Lin, M Yang, Y Wang, Z Wang 2023 Computing in Cardiology (CinC) 50, 1-4, 2023 | | 2023 |
| Raising High Risk-aware in Hemodynamic Treatment with Reinforcement Learning for Septic Shock Patients M Yang, R Li, T Hao, C Ma, J Li, C Liu 2022 Computing in Cardiology Conference (CinC) 49, 1-4, 2022 | | 2022 |
Chengyu LiuProfessor in Southeast University, ChinaBestätigte E-Mail-Adresse bei sdu.edu.cn