Recent trends and advances in fundus image analysis: A review
Automated retinal image analysis holds prime significance in the accurate diagnosis of
various critical eye diseases that include diabetic retinopathy (DR), age-related macular …
various critical eye diseases that include diabetic retinopathy (DR), age-related macular …
[HTML][HTML] AI recognition of patient race in medical imaging: a modelling study
Background Previous studies in medical imaging have shown disparate abilities of artificial
intelligence (AI) to detect a person's race, yet there is no known correlation for race on …
intelligence (AI) to detect a person's race, yet there is no known correlation for race on …
AI-integrated ocular imaging for predicting cardiovascular disease: advancements and future outlook
Cardiovascular disease (CVD) remains the leading cause of death worldwide. Assessing of
CVD risk plays an essential role in identifying individuals at higher risk and enables the …
CVD risk plays an essential role in identifying individuals at higher risk and enables the …
Reading race: AI recognises patient's racial identity in medical images
Background: In medical imaging, prior studies have demonstrated disparate AI performance
by race, yet there is no known correlation for race on medical imaging that would be obvious …
by race, yet there is no known correlation for race on medical imaging that would be obvious …
[HTML][HTML] The upcoming role of Artificial Intelligence (AI) for retinal and glaucomatous diseases
In recent years, the role of artificial intelligence (AI) and deep learning (DL) models is
attracting increasing global interest in the field of ophthalmology. DL models are considered …
attracting increasing global interest in the field of ophthalmology. DL models are considered …
Artificial intelligence in predicting systemic parameters and diseases from ophthalmic imaging
Artificial Intelligence (AI) analytics has been used to predict, classify, and aid clinical
management of multiple eye diseases. Its robust performances have prompted researchers …
management of multiple eye diseases. Its robust performances have prompted researchers …
Comparing code-free and bespoke deep learning approaches in ophthalmology
CYT Wong, C O'Byrne, P Taribagil, T Liu… - Graefe's Archive for …, 2024 - Springer
Aim Code-free deep learning (CFDL) allows clinicians without coding expertise to build high-
quality artificial intelligence (AI) models without writing code. In this review, we …
quality artificial intelligence (AI) models without writing code. In this review, we …
Use of artificial intelligence algorithms to predict systemic diseases from retinal images
The rise of non‐invasive, rapid, and widely accessible quantitative high‐resolution imaging
methods, such as modern retinal photography and optical coherence tomography (OCT) …
methods, such as modern retinal photography and optical coherence tomography (OCT) …
Artificial intelligence-based prediction of neurocardiovascular risk score from retinal swept-source optical coherence tomography–angiography
C Germanese, A Anwer, P Eid, LA Steinberg… - Scientific Reports, 2024 - nature.com
The recent rise of artificial intelligence represents a revolutionary way of improving current
medical practices, including cardiovascular (CV) assessment scores. Retinal vascular …
medical practices, including cardiovascular (CV) assessment scores. Retinal vascular …
Generative artificial intelligence in ophthalmology: multimodal retinal images for the diagnosis of Alzheimer's disease with convolutional neural networks
IR Slootweg, M Thach, KR Curro-Tafili… - arxiv preprint arxiv …, 2024 - arxiv.org
Background/Aim. This study aims to predict Amyloid Positron Emission Tomography
(AmyloidPET) status with multimodal retinal imaging and convolutional neural networks …
(AmyloidPET) status with multimodal retinal imaging and convolutional neural networks …