NCT06112886

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

Completed Last updated 2 November 2023

What this trial tests

trial testing There was no intervention in this study in Prediction Hypothyroidism Patients Using Machine Learning Algorithms in 1,296 participants. Completed in 20 September 2023.

Timeline

12 September 2022

Primary endpoint
12 September 2022

20 September 2023

Quick facts

Lead sponsor	Kerman University of Medical Sciences
Status	Completed
Study type	OBSERVATIONAL
Enrollment	1,296
Start date	12 September 2022
Primary completion	12 September 2022
Estimated completion	20 September 2023
Sites	1 location across Iran

Drugs / interventions tested

• There was no intervention in this study

Conditions studied

• Prediction Hypothyroidism Patients Using Machine Learning Algorithms — all drugs for Prediction Hypothyroidism Patients Using Machine Learning Algorithms →
• Identification of Important Symptoms of Hypothyroidism — all drugs for Identification of Important Symptoms of Hypothyroidism →

Sponsor

Kerman University of Medical Sciences

Who can join

18 and older, any sex, with Prediction Hypothyroidism Patients Using Machine Learning Algorithms or Identification of Important Symptoms of Hypothyroidism. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

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.

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

1. Identification of important symptoms and diagnostic hypothyroidism patients using machine learning algorithms
   Rakhshani Rad S, Mohammadi Z, Zadeh M, Mosleh-Shirazi M, et al · · 2024