Machine Learning Algorithm to predict insulin dosage for insulin-dependent Diabetics

Assessment of the Safety and Efficacy of a Novel Machine-learning Algorithm in the Management of Glycaemic Control in Insulin-Dependent Diabetics: A Randomised Controlled Clinical Trial - NIL

Status

Active, not recruiting

Phases

Phase 2Phase 3

Study type

Interventional

Source

CTRI

Registry ID

CTRI/2024/12/078673

Enrollment

Registered

2024-12-27

Start date

Unknown

Completion date

Unknown

Last updated

2025-02-03

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

Conditions

Health Condition 1: E119- Type 2 diabetes mellitus without complications

Interventions

Intervention1: Machine learning algorithm to predict insulin dosages for diabetic patients dependent on insulin for glycemic control: The ML algorithm runs on an app that auto-predicts the required in

Eligibility

Inclusion criteria

Inclusion criteria: Patients aged 18 years and above, but below 70 years of age and Clinically diagnosed T2DM and Patients already on insulin therapy as part of their DM therapy

Exclusion criteria

Exclusion criteria: Known hypersensitivity to insulin and Pregnant or lactating women and Patients above 70 years of age, or below 18 years of age and Comorbidities – Chronic Kidney Disease and T1DM patients on insulin therapy

Design outcomes

Primary

Measure	Time frame
Reduction in Hba1c levelTimepoint: 6 months	—

Secondary

Measure	Time frame
Other demographic factors that determine reduction in Hba1c between the two arms of the study.Timepoint: 6 months	—

Countries

India

Contacts

Public ContactDr. Noel Sam Thomas

Saveetha Medical College and Hospital

venkateswaran086@gmail.com9361249611

Outcome results

None listed

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