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Machine Learning-based Early Clinical Warning of High-risk Patients

NCT05410171 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 1000

Last updated 2022-12-01

No results posted yet for this study

Summary

Through the early warning platform for inpatients established by our hospital, the various indicators of patients collected in real time are carried out for automated intelligent evaluation and analysis, early warning of high-risk patients to assess the impact on patient prognosis and the impact on the occurrence of adverse events in inpatients.

Conditions

  • High-risk Patients
  • Risk Reduction
  • Machine Learning

Interventions

DEVICE

early warning platform

High risk inpatients will be evaluated by early warning platform

Sponsors & Collaborators

  • Southeast University, China

    lead OTHER

Principal Investigators

  • Songqiao Liu, PhD. · Zhongda Hospital, Southeast University, China

Study Design

Allocation
NON_RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Model
SEQUENTIAL

Eligibility

Min Age
18 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-06-01
Primary Completion
2023-06-01
Completion
2023-12-01

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05410171 on ClinicalTrials.gov