mlsanityData to 14 Oct 2026

Next-Generation Teleophthalmology: AI-enabled Quality Assessment Aiding Remote Smartphone-based Consultation

arXiv 2402.07118 ↗First posted 11 Feb 2024cs.HC cs.AI cs.LGcited by 0

Not on the map. Why?

Abstract (arXiv)

Blindness and other eye diseases are a global health concern, particularly in low- and middle-income countries like India. In this regard, during the COVID-19 pandemic, teleophthalmology became a lifeline, and the Grabi attachment for smartphone-based eye imaging gained in use. However, quality of user-captured image often remained inadequate, requiring clinician vetting and delays. In this backdrop, we propose an AI-based quality assessment system with instant feedback mimicking clinicians' judgments and tested on patient-captured images. Dividing the complex problem hierarchically, here we tackle a nontrivial part, and demonstrate a proof of the concept.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 8 references that are in the map. First posted on arXiv 11 Feb 2024.

Builds on

1 of 8 references.

References · 1

  1. 2022Extending F1 metric, probabilistic approachcited by 12

Built on by

Not cited yet.