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The capability of Artificial Intelligence in Predicting Thyroid Hormone without a Blood Test

Artificial Intelligence-based Clinical Decision Support System for Detecting Thyroid Hormone Levels from Handgrip Strength, Anthropometry, and Demographics - NIL

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2025/04/085984
Enrollment
400
Registered
2025-04-29
Start date
Unknown
Completion date
Unknown
Last updated
2025-05-26

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

Conditions

Health Condition 1: E02- Subclinical iodine-deficiency hypothyroidism

Interventions

Intervention1: Nil: Nil Intervention2: Nil: Nil Control Intervention1: Nil: Nil

Sponsors

Himel Mondal
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Hospital-based convenience sample. The sample would be recruited from the Department of Medicine, suspected of thyroid disorders. A total of 30 individual from each age group of 18 - 21 years, 22 - 25 years, 26 - 29 years, 30 - 33 years, 34 - 37 years, 38 - 41 years, 42 - 45 years, 46 - 49 years, 50 - 53 years, and 54 - 60 years.

Exclusion criteria

Exclusion criteria: Any individual with known diabetes mellitus, having any known neuromuscular disease, having any known hormonal imbalance, any recent injury or surgeries would be excluded from the study. Pregnant women will be excluded.

Design outcomes

Primary

MeasureTime frame
A machine learning model with possible capability of predicting thyroid hormone level from anthropometric and demographic data.Timepoint: Baseline—

Secondary

MeasureTime frame
NILTimepoint: NIL—

Countries

India

Contacts

Public ContactDr Himel Mondal

All India Institute of Medical Sciences, Deoghar

himelmkcg@gmail.com919830293119

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026