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Machine Learning for Reclassification of Obesity

NCT04282837 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 2495

Last updated 2020-06-25

No results posted yet for this study

Summary

The goal of this study is to employ or develop computational modeling techniques for the precise reclassification of obesity into subgroups. Clinical features, risks of noncommunicable diseases, as well as weight loss effects of bariatric surgery will also be studied and compared within the subgroups.

Conditions

Interventions

DIAGNOSTIC_TEST

AI classification of patients with obesity

Computational modeling techniques will be used for the precise reclassification of obesity into four subgroups, several variables according to the clinical experience and the modeling results will be selected for the cluster analysis.

Sponsors & Collaborators

  • The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School

    collaborator OTHER

  • The Third People's Hospital of Chengdu

    collaborator OTHER

  • Shanghai East Hospital

    collaborator OTHER

  • University of Pittsburgh

    collaborator OTHER

  • Shanghai 10th People's Hospital

    lead OTHER

Eligibility

Min Age
10 Years
Max Age
70 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2020-03-01
Primary Completion
2020-04-30
Completion
2020-06-20

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

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 NCT04282837 on ClinicalTrials.gov