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Identification of Important Symptoms and Diagnostic Hypothyroidism Patients Using Machine Learning Algorithms

NCT06112886 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1296

Last updated 2023-11-02

No results posted yet for this study

Summary

Hypothyroidism (HT) is one of the most common endocrine diseases. It is, however, usually challenging for physicians to diagnose due to non-specific symptoms. The usual procedure for diagnosis of HT is a blood test. In recent years, machine learning algorithms have proved to be powerful tools in medicine due to their diagnostic accuracy. In this study, we aim to predict and identify the most important symptoms of HT using machine learning algorithms.

Conditions

  • Prediction Hypothyroidism Patients Using Machine Learning Algorithms
  • Identification of Important Symptoms of Hypothyroidism

Interventions

OTHER

There was no intervention in this study

There was no intervention in this study

Sponsors & Collaborators

  • Kerman University of Medical Sciences

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-09-12
Primary Completion
2022-09-12
Completion
2023-09-20

Countries

  • Iran

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 NCT06112886 on ClinicalTrials.gov