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Study identifier: NCT07070362 Synced from ClinicalTrials.gov · July 28, 2026
● Recruiting

Digital Early Warning System for Acute Lung Injury in Liver Surgery

Condition: Acute Lung Injury(ALI) · Liver Cirrhosis · ARDS, Human  ·  Sponsor: Beijing Tsinghua Chang Gung Hospital

PhaseN/A
Planned participants4000
Who can joinAll sexes, 18 Years to no upper limit
Healthy volunteersNo

About this study

This study focuses on developing an explainable machine learning model based on cardiopulmonary interaction characteristics to achieve early prediction of acute lung injury (ALI) in patients undergoing major liver surgery. The research will establish a digital early-warning system for ALI to provide support for clinical diagnosis and treatment decisions, thereby reducing the incidence and fatality rate of ALI.

This description comes directly from the study's public registry record.

Talk to the study team

Gao Zhifeng, MD  ·  +8615801249466  ·  btchgzf@hotmail.com

Always discuss trial participation with your own doctor first.

Locations (1)

Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine,Tsinghua UniversityBeijing, Beijing Municipality, ChinaRecruiting

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Source record: clinicaltrials.gov/study/NCT07070362