PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 3, 20260 citations

The artificial intelligence driven on the development of diabetic retinopathy prognostic scoring tool among type 2 diabetes mellitus patients: A review.

MTM M S TerunaTRT R RazakSYS M Yasin

Key Points

  • AI-driven tools enhance early risk prediction for diabetic retinopathy, improving patient outcomes.
  • Current tools require broader external validation to ensure reliability across various populations.
  • Effective calibration of prognostic models is crucial for accurate risk assessments in diverse patient groups.
  • Routine clinical adoption hinges on successful validation of these AI-driven tools in real-world settings.

Abstract

AI-driven prognostic tools show strong potential to enhance early diabetic retinopathy risk prediction. However, broader external validation and population-specific calibration are needed before routine clinical adoption.

Ask AI
Helpful
Bookmark
Share

Cite This Study

Teruna et al. (2026) studied this question.

synapsesocial.com/papers/69a75fa6c6e9836116a2b2d7
Ask AI
Helpful
Bookmark
Share