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Digital Early Warning System for Acute Lung Injury in Liver Surgery

RECRUITINGSponsored by Beijing Tsinghua Chang Gung Hospital
Actively Recruiting
SponsorBeijing Tsinghua Chang Gung Hospital
Started2024-11-01
Est. completion2027-06-01
Eligibility
Age18 Years+
Healthy vol.Accepted
View on ClinicalTrials.gov →

NCT07070362

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.

Eligibility

Age: 18 Years+Healthy volunteers accepted
Inclusion Criteria:

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

Conditions11

ARDS, HumanAcute Lung Injury(ALI)CancerLiver CancerLiver Cancer, AdultLiver CirrhosisLiver DiseaseLung CancerMASLDMASLD/MASH (Metabolic Dysfunction-Associated Steatotic Liver Disease / Metabolic Dysfunction-Associated Steatohepatitis)

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