One-year access to more than 500 world journals available in the system
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http://medilib.ir
- Duration of Time : 365 Day
Price : 300$- Special Price : 100$
Journals package 3months
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http://medilib.ir
- Duration of Time : 93 Day
Price : 100$- Special Price : 50$
Generative artificial intelligence in ophthalmology: current innovations, future applications and challenges
doi : 10.1136/bjo-2024-325458
Towards regulatory generative AI in ophthalmology healthcare: a security and privacy perspective
doi : 10.1136/bjo-2024-325167
Medical education with large language models in ophthalmology: custom instructions and enhanced retrieval capabilities
doi : 10.1136/bjo-2023-325046
Review of emerging trends and projection of future developments in large language models research in ophthalmology
doi : 10.1136/bjo-2023-324734
Capabilities of GPT-4 in ophthalmology: an analysis of model entropy and progress towards human-level medical question answering
doi : 10.1136/bjo-2023-324438
Performance of ChatGPT and Bard on the official part 1 FRCOphth practice questions
doi : 10.1136/bjo-2023-324091
Unveiling the clinical incapabilities: a benchmarking study of GPT-4V(ision) for ophthalmic multimodal image analysis
doi : 10.1136/bjo-2023-325054
Development and evaluation of a large language model of ophthalmology in Chinese
doi : 10.1136/bjo-2023-324526
Assessing the medical reasoning skills of GPT-4 in complex ophthalmology cases
doi : 10.1136/bjo-2023-325053
Deep learning model for extensive smartphone-based diagnosis and triage of cataracts and multiple corneal diseases
doi : 10.1136/bjo-2023-324488
Creating realistic anterior segment optical coherence tomography images using generative adversarial networks
doi : 10.1136/bjo-2023-324633
Digital ray: enhancing cataractous fundus images using style transfer generative adversarial networks to improve retinopathy detection
doi : 10.1136/bjo-2024-325403
Using artificial intelligence to improve human performance: efficient retinal disease detection training with synthetic images
doi : 10.1136/bjo-2023-324923
Validation of a deep learning model for automatic detection and quantification of five OCT critical retinal features associated with neovascular age-related macular degeneration
doi : 10.1136/bjo-2023-324647
Comparing generative and retrieval-based chatbots in answering patient questions regarding age-related macular degeneration and diabetic retinopathy
doi : 10.1136/bjo-2023-324533
ICGA-GPT: report generation and question answering for indocyanine green angiography images
doi : 10.1136/bjo-2023-324446
Exploring AI-chatbots’ capability to suggest surgical planning in ophthalmology: ChatGPT versus Google Gemini analysis of retinal detachment cases
doi : 10.1136/bjo-2023-325143
Large language models: a new frontier in paediatric cataract patient education
doi : 10.1136/bjo-2024-325252
