Skip to main content
TrialFinder
TrialFinder is for informational purposes only and does not provide medical advice. Always talk to your doctor about whether a trial is right for you.
RECRUITINGOBSERVATIONAL

Digital Early Warning System for Acute Lung Injury in Liver Surgery

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

Important: This information is not medical advice. Talk to your doctor about whether a clinical trial is right for you.

About This Trial

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.

Who May Be Eligible (Plain English)

Who May Qualify: - Age ≥ 18 years - Undergoing major liver surgery (including two-segment or more hepatectomy, liver transplantation, etc.) - Voluntary participation with signed willing to sign a consent form Always talk to your doctor about whether this trial is right for you.

Original Eligibility Criteria

View original clinical language
Inclusion Criteria: * Age ≥ 18 years * Undergoing major liver surgery (including two-segment or more hepatectomy, liver transplantation, etc.) * Voluntary participation with signed informed consent

Treatments Being Tested

OTHER

None-placebo

This observational cohort study is non-interventional. Perioperative treatment plans are made based on model - suggested results and anesthesiologists' thought processes, without adding new medicines for patients.

Locations (1)

Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine，Tsinghua University
Beijing, Beijing Municipality, China