Machine Learning to Dynamically Predict In-Hospital Venous Thromboembolism After Inguinal Hernia Surgery: Results From the CHAT-1 Study.

Yi-Dan YanZe YuLan-Ping DingMin ZhouChi ZhangMang-Mang PanJin-Yuan ZhangZe-Yuan WangFei GaoHang-Yu LiGuang-Yong ZhangHou-Wen LinMing-Gang WangZhi-Chun Gu

Published in: Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis (2023)

A ML-based approach for the identification of in-hospital VTE events after hernia surgery is feasible. TabNet showed acceptable performance, and might be useful to guide clinical decision making and VTE prevention. Further validated study will strengthen this finding.

Keyphrases

venous thromboembolism
machine learning
minimally invasive
healthcare
decision making
direct oral anticoagulants
emergency department
big data
adverse drug