Development and validation of a deep interpretable network for continuous acute kidney injury prediction in critically ill patients

Meicheng Yang, Songqiao Liu, Tong Hao, Caiyun Ma, Hui Chen, Yuwen Li, Changde Wu, Jianfeng Xie, Haibo Qiu, Jianqing Li, Yi Yang, Chengyu Liu

Abstract: Highlights•A deep neural network developed for continuously predicting the 24-hour AKI risk•The model interpretability help the understanding of AKI risk at individual patient levels•Generalisability in AI-based models is important when deployed in real-world settings