AI Medical Compendium Topic

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Retinal Diseases

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A deep learning framework for the early detection of multi-retinal diseases.

PloS one
Retinal images play a pivotal contribution to the diagnosis of various ocular conditions by ophthalmologists. Extensive research was conducted to enable early detection and timely treatment using deep learning algorithms for retinal fundus images. Qu...

Protocol for performing deep learning-based fundus fluorescein angiography image analysis with classification and segmentation tasks.

STAR protocols
Fundus fluorescein angiography (FFA) examinations are widely used in the evaluation of fundus disease conditions to facilitate further treatment suggestions. Here, we present a protocol for performing deep learning-based FFA image analytics with clas...

Artificial intelligence for retinal diseases.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: To discuss the worldwide applications and potential impact of artificial intelligence (AI) for the diagnosis, management and analysis of treatment outcomes of common retinal diseases.

[The innovation and challenge of artificial intelligence in the whole process management of fundus disease].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
Artificial intelligence (AI) has demonstrated revolutionary potential and wide-ranging applications in the comprehensive management of fundus diseases, yet it faces challenges in clinical translation, data quality, algorithm interpretability, and cro...

A hybrid model for the detection of retinal disorders using artificial intelligence techniques.

Biomedical physics & engineering express
The prevalence of vision impairment is increasing at an alarming rate. The goal of the study was to create an automated method that uses optical coherence tomography (OCT) to classify retinal disorders into four categories: choroidal neovascularizati...

ChatGPT and retinal disease: a cross-sectional study on AI comprehension of clinical guidelines.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: To evaluate the performance of an artificial intelligence (AI) large language model, ChatGPT (version 4.0), for common retinal diseases, in accordance with the American Academy of Ophthalmology (AAO) Preferred Practice Pattern (PPP) guidel...

Role of Artificial Intelligence in Retinal Diseases.

Klinische Monatsblatter fur Augenheilkunde
Artificial intelligence (AI) has already found its way into ophthalmology, with the first approved algorithms that can be used in clinical routine. Retinal diseases in particular are proving to be an important area of application for AI, as they are ...

SCINet: A Segmentation and Classification Interaction CNN Method for Arteriosclerotic Retinopathy Grading.

Interdisciplinary sciences, computational life sciences
As a common disease, cardiovascular and cerebrovascular diseases pose a great harm threat to human wellness. Even using advanced and comprehensive treatment methods, there is still a high mortality rate. Arteriosclerosis, as an important factor refle...

DualStreamFoveaNet: A Dual Stream Fusion Architecture With Anatomical Awareness for Robust Fovea Localization.

IEEE journal of biomedical and health informatics
Accurate fovea localization is essential for analyzing retinal diseases to prevent irreversible vision loss. While current deep learning-based methods outperform traditional ones, they still face challenges such as the lack of local anatomical landma...

Label-Aware Dual Graph Neural Networks for Multi-Label Fundus Image Classification.

IEEE journal of biomedical and health informatics
Fundus disease is a complex and universal disease involving a variety of pathologies. Its early diagnosis using fundus images can effectively prevent further diseases and provide targeted treatment plans for patients. Recent deep learning models for ...