Results 11 to 20 of about 664,169 (399)
Learnable Ophthalmology SAM [PDF]
arXiv, 2023 Segmentation is vital for ophthalmology image analysis. But its various modal images hinder most of the existing segmentation algorithms applications, as they rely on training based on a large number of labels or hold weak generalization ability. Based on Segment Anything (SAM), we propose a simple but effective learnable prompt layer suitable for ...
Zhongxi Qiu, Yan Hu, Heng Li, Jiang Liu
arxiv +3 more sources
Ophthalmology and Social Media: An In-Depth Investigation of Ophthalmologic Content on Instagram
Clinical Ophthalmology, 2022 Andy S Huang,1 Ali Adel Ne’ma Abdullah,2 Kelsey Chen,3 Dagny Zhu4 1Medical College of Georgia, Augusta, GA, USA; 2St Helier Hospital, Sutton, London, UK; 3Midwestern University, Glendale, AZ, USA; 4Hyperspeed LASIK/NVISION Eye Centers, Rowland Heights ...
Huang AS, Abdullah AAN, Chen K, Zhu D
doaj +2 more sources
Evaluating the Performance of ChatGPT in Ophthalmology
medRxiv, 2023 We tested the accuracy of ChatGPT, a large language model (LLM), in the ophthalmology question-answering space using two popular multiple choice question banks used for the high-stakes Ophthalmic Knowledge Assessment Program (OKAP) exam. The testing sets
F. Antaki +4 more
semanticscholar +1 more source
Cureus, 2023 Importance Chat Generative Pre-Trained Transformer (ChatGPT) has shown promising performance in various fields, including medicine, business, and law, but its accuracy in specialty-specific medical questions, particularly in ophthalmology, is still ...
M. Moshirfar +4 more
semanticscholar +1 more source
Medicina, 2023 Medical imaging is the mainstay of clinical diagnosis and management. Optical coherence tomography (OCT) is a non-invasive imaging technology that has revolutionized the field of ophthalmology.
Marco Zeppieri +7 more
semanticscholar +1 more source
Journal of Academic Ophthalmology, 2021 Objective The study aimed to investigate factors influencing choice of specialty among ophthalmology and non-ophthalmology residency applicants. Patients and Methods Anonymous, web-based surveys were distributed through REDCap to the 2019 to ...
David Cui +2 more
doaj +1 more source
Application of generative adversarial networks (GAN) for ophthalmology image domains: a survey
Eye and Vision, 2022 Background Recent advances in deep learning techniques have led to improved diagnostic abilities in ophthalmology. A generative adversarial network (GAN), which consists of two competing types of deep neural networks, including a generator and a ...
Aram You, Jin Kuk Kim, I. Ryu, T. Yoo
semanticscholar +1 more source
British Journal of Ophthalmology, 2022 Natural language processing (NLP) is a subfield of machine intelligence focused on the interaction of human language with computer systems. NLP has recently been discussed in the mainstream media and the literature with the advent of Generative Pre ...
Siddharth Nath +4 more
semanticscholar +1 more source
Frontiers in Molecular Biosciences, 2021 Pseudoexfoliation syndrome (XFS) is stress- or inflammation-induced elastosis accompanied by excessive production of microfibrils and their deposition in the anterior segment of the eye.
Diana Anna Dmuchowska +9 more
doaj +1 more source