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Digital Early Warning System for Acute Lung Injury in Liver Surgery
Sponsor: Beijing Tsinghua Chang Gung Hospital
Summary
This study aims to develop an explainable machine learning model that takes into account the characteristics of cardiopulmonary interactions. This model will enable early prediction of acute lung injury (ALI) in patients undergoing major liver surgery. The research will create a digital early-warning system for ALI, thereby supporting clinical diagnosis and treatment decisions. This, in turn, should help reduce the incidence and mortality rates associated with ALI.
Official title: The Construction of a Digital Intelligence Early Warning System for the Whole Process of Acute Lung Injury in Liver Surgery Based on Cardiopulmonary Interaction Characteristics
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
3000
Start Date
2024-11-01
Completion Date
2027-11-30
Last Updated
2026-08-17
Healthy Volunteers
No
Conditions
Locations (4)
Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine，Tsinghua University
Beijing, Beijing Municipality, China
Peking University International Hospital
Beijing, China
Southwest Hospital, The First Affiliated Hospital of Army Medical University
Chongqing, China
Huangdao District People's Hospital of Qingdao
Qingdao, China