Real World Analysis of Two Handheld Retinograph, Evaluation by Ophthalmologist and an Artificial Intelligence Algorithm

How to cite: Romero‐Aroca, P.; Fontova‐Poveda, B.; Garcia‐Curto, E.; Valls, A.; Cristiano, J.; Llagostera‐Serra, M.; Morente‐Lorenzo, C.; Mendez‐Marín, I.; Baget‐Bernaldiz, M. Real World Analysis of Two Handheld Retinograph, Evaluation by Ophthalmologist and an Artificial Intelligence Algorithm. Preprints 2024, 2024090814. https://doi.org/10.20944/preprints202409.0814.v1 Romero‐Aroca, P.; Fontova‐Poveda, B.; Garcia‐Curto, E.; Valls, A.; Cristiano, J.; Llagostera‐Serra, M.; Morente‐Lorenzo, C.; Mendez‐Marín, I.; Baget‐Bernaldiz, M. Real World Analysis of Two Handheld Retinograph, Evaluation by Ophthalmologist and an Artificial Intelligence Algorithm. Preprints 2024, 2024090814. https://doi.org/10.20944/preprints202409.0814.v1

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MDPI and ACS Style

Romero‐Aroca, P.; Fontova‐Poveda, B.; Garcia‐Curto, E.; Valls, A.; Cristiano, J.; Llagostera‐Serra, M.; Morente‐Lorenzo, C.; Mendez‐Marín, I.; Baget‐Bernaldiz, M. Real World Analysis of Two Handheld Retinograph, Evaluation by Ophthalmologist and an Artificial Intelligence Algorithm. Preprints 2024, 2024090814. https://doi.org/10.20944/preprints202409.0814.v1

APA Style

Romero‐Aroca, P., Fontova‐Poveda, B., Garcia‐Curto, E., Valls, A., Cristiano, J., Llagostera‐Serra, M., Morente‐Lorenzo, C., Mendez‐Marín, I., & Baget‐Bernaldiz, M. (2024). Real World Analysis of Two Handheld Retinograph, Evaluation by Ophthalmologist and an Artificial Intelligence Algorithm. Preprints. https://doi.org/10.20944/preprints202409.0814.v1

Chicago/Turabian Style

Romero‐Aroca, P., Isabel Mendez‐Marín and Marc Baget‐Bernaldiz. 2024 "Real World Analysis of Two Handheld Retinograph, Evaluation by Ophthalmologist and an Artificial Intelligence Algorithm" Preprints. https://doi.org/10.20944/preprints202409.0814.v1

Abstract

(1) Telemedicine in diabetic retinopathy (RD) screening is effective but does not reach the entire diabetes population. The use of portable cameras and artificial intelligence (AI) can help diabetes screening. (2) Methods: We evaluated the ability of two handheld cameras, one based on a smartphone and the other on a smartscope, to obtain images comparing OCT. Evaluation was done in two stages, the first by two retina specialists and the second using an artificial intelligence algorithm that we developed. (3) Results: The retina specialists report that the smartphone images must mydriasis in all cases compared to 73.05% of the smartscope images and 71.11% of the OCT images. Images were ungradable in 27.98% of the retinographs with the smartphone and 7.98% with the smartscope. The detection of any-DR using the AI algorithm showed that the smartphone obtained lower recall values (0.89) and F1scores (0.89) than the smartscope, with 0.99. The detection of Mild-DR using the smartphone also obtained low results (146 retinographs) compared to the smartscope (218 retinographs). (4) Conclusions: The use of handheld devices together with AI algorithms for reading retinographs can be useful for DR screening, although these devices need to improve the ease image acquisition through small pupils.

Keywords

artificial intelligence; diabetic retinopathy; handheld retinal camera; public health; screening; smartphones; telemedicine; image quality

Subject

Medicine and Pharmacology, Ophthalmology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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