Evaluation of artificial intelligence generated responses of commonly asked ophthalmic queries

Purpose: To evaluate artificial intelligence generated responses of commonly asked ophthalmic queries. Methods: In this study, 10 common questions related to ophthalmic conditions were prepared by experienced ophthalmologists based on common queries by patients in India. The responses to these questions were obtained from ChatGPT. The responses were scored for accuracy, completeness, and understandability by two experienced unacquainted ophthalmologists. Results: In this study, mean values of overall scores for accuracy, completeness, understandability of ChatGPT responses graded fair (mean scores of 3.25 ± 0.75, 1.95 ± 1.5 and 2.3 ± 0.7, respectively). Understandability of responses to surgery related queries were significantly low compared to non-surgical ones ( P = 0.041). Conclusions: Study findings indicate ChatGPT’s responses to overall accuracy, completeness and understandability were just fair, suggesting ChatGPT offers information to some extent, but it falls short of expert ophthalmologist’s level.

Authors

Institutions

Publication Details

Journal
Kerala Journal of Ophthalmology
Published
2025-09-01
DOI
https://doi.org/10.4103/kjo.kjo_26_25
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluation of artificial intelligence generated responses of commonly asked ophthalmic queries

Mahesh Babu, B Sumanth, Shruthi Konatham
Kerala Journal of Ophthalmology
Artificial Intelligence in Healthcare and Education
article

Evaluation of artificial intelligence generated responses of commonly asked ophthalmic queries

Mahesh Babu, B Sumanth, Shruthi Konatham
article en

Abstract

Purpose: To evaluate artificial intelligence generated responses of commonly asked ophthalmic queries. Methods: In this study, 10 common questions related to ophthalmic conditions were prepared by experienced ophthalmologists based on common queries by patients in India. The responses to these questions were obtained from ChatGPT. The responses were scored for accuracy, completeness, and understandability by two experienced unacquainted ophthalmologists. Results: In this study, mean values of overall scores for accuracy, completeness, understandability of ChatGPT responses graded fair (mean scores of 3.25 ± 0.75, 1.95 ± 1.5 and 2.3 ± 0.7, respectively). Understandability of responses to surgery related queries were significantly low compared to non-surgical ones ( P = 0.041). Conclusions: Study findings indicate ChatGPT’s responses to overall accuracy, completeness and understandability were just fair, suggesting ChatGPT offers information to some extent, but it falls short of expert ophthalmologist’s level.

Kerala Journal of OphthalmologyVol. 37(3)
KVG Medical College & Hospital (IN)
Quality Education
Openalex Percentile: Top 39%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.