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

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

Status
UNKNOWN
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT05410171
Enrollment
1000
Registered
2022-06-08
Start date
2022-06-01
Completion date
2023-12-01
Last updated
2022-12-01

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

High-risk Patients, Machine Learning, Risk Reduction

Brief 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.

Detailed description

Build the early warning system.

Interventions

DEVICEearly warning platform

High risk inpatients will be evaluated by early warning platform

Sponsors

Southeast University, China
Lead SponsorOTHER

Study design

Allocation
NON_RANDOMIZED
Intervention model
SEQUENTIAL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
No

Inclusion criteria

1. Patients who use ECG monitoring 2. Age ≥ 18 years old 3. Understand and sign an informed consent form

Exclusion criteria

* Pregnancy or lactation

Design outcomes

Primary

MeasureTime frameDescription
28-day all cause mortality28 days28-day all cause mortality

Secondary

MeasureTime frameDescription
Hospital mortalitythrough study completion, an average of 1 monthHospital mortality

Countries

China

Contacts

Primary ContactChangde Wu
liusongqiao@ymail.com086-02583262550

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026