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Machine Learning for Early Diagnosis of Endometriosis(MLEndo)

NCT06147687 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 10000

Last updated 2023-11-28

No results posted yet for this study

Summary

The project aims to create a large prospective data bank using the Lucy medical mobile application and collect and analyze patient profiles and structured clinical data with artificial intelligence. In addition, authors will investigate the association of removed or restricted dietary components with quality of life, pain, and central sensitization.

Conditions

  • Endometriosis
  • Pelvic Pain
  • Infertility, Female

Interventions

DIAGNOSTIC_TEST

Self reported data collection

ML assessement of colleceted data

Sponsors & Collaborators

  • University of Aarhus

    collaborator OTHER

  • Semmelweis University

    lead OTHER

Principal Investigators

  • Attila Bokor · Semmelweis University

Eligibility

Min Age
14 Years
Max Age
45 Years
Sex
FEMALE
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-01-01
Primary Completion
2024-12-31
Completion
2024-12-31

Countries

  • Hungary

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 NCT06147687 on ClinicalTrials.gov