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] Generative artificial intelligence through ChatGPT and other large language models in ophthalmology: clinical applications and challenges
The rapid progress of large language models (LLMs) driving generative artificial intelligence
applications heralds the potential of opportunities in health care. We conducted a review up …
applications heralds the potential of opportunities in health care. We conducted a review up …
Machine learning as a tool for hypothesis generation
While hypothesis testing is a highly formalized activity, hypothesis generation remains
largely informal. We propose a systematic procedure to generate novel hypotheses about …
largely informal. We propose a systematic procedure to generate novel hypotheses about …
Toward fairness in artificial intelligence for medical image analysis: identification and mitigation of potential biases in the roadmap from data collection to model …
Purpose To recognize and address various sources of bias essential for algorithmic fairness
and trustworthiness and to contribute to a just and equitable deployment of AI in medical …
and trustworthiness and to contribute to a just and equitable deployment of AI in medical …
[HTML][HTML] Analysis of various techniques for ECG signal in healthcare, past, present, and future
Cardiovascular diseases are the primary reason for mortality worldwide. As per WHO survey
report in 2019, 17.9 million people died due to CVDs, accounting for 32% of all global …
report in 2019, 17.9 million people died due to CVDs, accounting for 32% of all global …
Performance of automated machine learning for diabetic retinopathy image classification from multi-field handheld retinal images
CMP Jacoba, D Doan, RP Salongcay, LAC Aquino… - Ophthalmology …, 2023 - Elsevier
Purpose To create and validate code-free automated deep learning models (AutoML) for
diabetic retinopathy (DR) classification from handheld retinal images. Design Prospective …
diabetic retinopathy (DR) classification from handheld retinal images. Design Prospective …
Smartphone eye examination: artificial intelligence and telemedicine
MAP Vilela, A Arrigo, MB Parodi… - Telemedicine and e …, 2024 - liebertpub.com
Background: The current medical scenario is closely linked to recent progress in
telecommunications, photodocumentation, and artificial intelligence (AI). Smartphone eye …
telecommunications, photodocumentation, and artificial intelligence (AI). Smartphone eye …
Federated learning in ocular imaging: current progress and future direction
Advances in artificial intelligence deep learning (DL) have made tremendous impacts on the
field of ocular imaging over the last few years. Specifically, DL has been utilised to detect …
field of ocular imaging over the last few years. Specifically, DL has been utilised to detect …
Accuracy of automated machine learning in classifying retinal pathologies from ultra-widefield pseudocolour fundus images
Aims Automated machine learning (AutoML) is a novel tool in artificial intelligence (AI). This
study assessed the discriminative performance of AutoML in differentiating retinal vein …
study assessed the discriminative performance of AutoML in differentiating retinal vein …
Bias and Non-Diversity of Big Data in Artificial Intelligence: Focus on Retinal Diseases: “Massachusetts Eye and Ear Special Issue”
Artificial intelligence (AI) applications in healthcare will have a potentially far-reaching
impact on patient care, however issues regarding algorithmic bias and fairness have …
impact on patient care, however issues regarding algorithmic bias and fairness have …