Clinical Research Directory

Browse clinical research sites, groups, and studies.

Sites Groups Studies

Back to Studies

RECRUITING

NCT07070362

Digital Early Warning System for Acute Lung Injury in Liver Surgery

Sponsor: Beijing Tsinghua Chang Gung Hospital

View on ClinicalTrials.gov

Summary

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.

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

4000

Start Date

2024-11-01

Completion Date

2027-11-30

Last Updated

2025-07-17

Healthy Volunteers

Conditions

Acute Lung Injury(ALI)Liver Cirrhosis ARDS, Human MASLD MASLD/MASH (Metabolic Dysfunction-Associated Steatotic Liver Disease / Metabolic Dysfunction-Associated Steatohepatitis)NAFLD (Nonalcoholic Fatty Liver Disease)Liver Cancer, Adult

Interventions

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