RETINA ANALYSIS APP

The Retina Image Analysis Android Application is an AI-powered mobile health (mHealth) solution designed to assist users in the early detection of retina-related disorders through deep learning and interactive guidance. Developed using Java/XML for Android and integrated with Firebase Realtime Database and Authentication, the app allows users to upload retina images from their device gallery and complete a symptom-based questionnaire. The core diagnostic process utilizes a Convolutional Neural Network (CNN) model deployed via TensorFlow Lite, which classifies retina images into disease categories and generates confidence scores in real-time. To enhance interpretability and user support, the application includes an NLP-based chatbot assistant that responds to natural language queries, explains disease outcomes, and offers customized recommendations. The system further employs the Google Maps API to identify and display nearby retina specialists and eye hospitals based on the user's location, thus bridging the gap between digital diagnosis and clinical consultation. This solution demonstrates how mobile AI, when combined with cloud-based data handling, chatbot interaction, and geolocation services, can empower patients with accurate health insights, promote early intervention, and reduce dependency on in-person screenings, especially in remote or underserved regions.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-06
DOI
https://doi.org/10.5281/zenodo.15608053
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

RETINA ANALYSIS APP

Zenodo (CERN European Organization for Nuclear Research)
Retinal Imaging and Analysis
article

RETINA ANALYSIS APP

article en

Abstract

The Retina Image Analysis Android Application is an AI-powered mobile health (mHealth) solution designed to assist users in the early detection of retina-related disorders through deep learning and interactive guidance. Developed using Java/XML for Android and integrated with Firebase Realtime Database and Authentication, the app allows users to upload retina images from their device gallery and complete a symptom-based questionnaire. The core diagnostic process utilizes a Convolutional Neural Network (CNN) model deployed via TensorFlow Lite, which classifies retina images into disease categories and generates confidence scores in real-time. To enhance interpretability and user support, the application includes an NLP-based chatbot assistant that responds to natural language queries, explains disease outcomes, and offers customized recommendations. The system further employs the Google Maps API to identify and display nearby retina specialists and eye hospitals based on the user's location, thus bridging the gap between digital diagnosis and clinical consultation. This solution demonstrates how mobile AI, when combined with cloud-based data handling, chatbot interaction, and geolocation services, can empower patients with accurate health insights, promote early intervention, and reduce dependency on in-person screenings, especially in remote or underserved regions.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 40%
Retinal Imaging and Analysis
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.