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Artificial Intelligence in Diabetes Care and Prevention (103) Clinical Information and Decision Making (3544) Quality/Credibility of eHealth Information and Trust Issues (925) Diabetes Education and Elearning for Patients (201) Artificial Intelligence (4549)

Published on in Vol 11 (2026)

This is a member publication of Imperial College London (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/93822, first published .
Scientist in lab coat uses tablet, with microscope and computer screen in background.

Assessing Quality, Readability, and Transparency of Online and AI-Generated Information on Type 2 Diabetes Mellitus: Cross-Sectional Exploratory Study

Assessing Quality, Readability, and Transparency of Online and AI-Generated Information on Type 2 Diabetes Mellitus: Cross-Sectional Exploratory Study

Authors of this article:

Sripradha Srinivasan1 Author Orcid Image ;   Ravanth Baskaran1, 2 Author Orcid Image ;   Srinjay Mukhopadhyay3, 4 Author Orcid Image ;   Mayank Patel1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Sripradha Srinivasan   1 , MBBCh ;   Ravanth Baskaran   1, 2 , MBBCh ;   Srinjay Mukhopadhyay   3, 4 , BSc, MBBCh ;   Mayank Patel   1 , BM, DM

1 University Hospital Southampton NHS Foundation Trust, Southampton, England, United Kingdom

2 School of Medicine, Cardiff University, Cardiff, Wales, United Kingdom

3 National Heart and Lung Institute, Imperial College London, London, United Kingdom

4 Imperial College Healthcare NHS Trust, London, England, United Kingdom

Corresponding Author:

  • Srinjay Mukhopadhyay, BSc, MBBCh
  • Imperial College Healthcare NHS Trust
  • The Bays, S Wharf Rd
  • London, England W2 1NY
  • United Kingdom
  • Phone: 44 02033113311
  • Email: sm1722@ic.ac.uk