AIMC Topic: Ophthalmology

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Generative artificial intelligence in ophthalmology: current innovations, future applications and challenges.

The British journal of ophthalmology
The rapid advancements in generative artificial intelligence are set to significantly influence the medical sector, particularly ophthalmology. Generative adversarial networks and diffusion models enable the creation of synthetic images, aiding the d...

Foundation models in ophthalmology.

The British journal of ophthalmology
Foundation models represent a paradigm shift in artificial intelligence (AI), evolving from narrow models designed for specific tasks to versatile, generalisable models adaptable to a myriad of diverse applications. Ophthalmology as a specialty has t...

Towards regulatory generative AI in ophthalmology healthcare: a security and privacy perspective.

The British journal of ophthalmology
As the healthcare community increasingly harnesses the power of generative artificial intelligence (AI), critical issues of security, privacy and regulation take centre stage. In this paper, we explore the security and privacy risks of generative AI ...

Medical education with large language models in ophthalmology: custom instructions and enhanced retrieval capabilities.

The British journal of ophthalmology
Foundation models are the next generation of artificial intelligence that has the potential to provide novel use cases for healthcare. Large language models (LLMs), a type of foundation model, are capable of language comprehension and the ability to ...

Using artificial intelligence to improve human performance: efficient retinal disease detection training with synthetic images.

The British journal of ophthalmology
BACKGROUND: Artificial intelligence (AI) in medical imaging diagnostics has huge potential, but human judgement is still indispensable. We propose an AI-aided teaching method that leverages generative AI to train students on many images while preserv...

Assessing the medical reasoning skills of GPT-4 in complex ophthalmology cases.

The British journal of ophthalmology
BACKGROUND/AIMS: This study assesses the proficiency of Generative Pre-trained Transformer (GPT)-4 in answering questions about complex clinical ophthalmology cases.

Performance of ChatGPT and Bard on the official part 1 FRCOphth practice questions.

The British journal of ophthalmology
BACKGROUND: Chat Generative Pre-trained Transformer (ChatGPT), a large language model by OpenAI, and Bard, Google's artificial intelligence (AI) chatbot, have been evaluated in various contexts. This study aims to assess these models' proficiency in ...

Capabilities of GPT-4 in ophthalmology: an analysis of model entropy and progress towards human-level medical question answering.

The British journal of ophthalmology
BACKGROUND: Evidence on the performance of Generative Pre-trained Transformer 4 (GPT-4), a large language model (LLM), in the ophthalmology question-answering domain is needed.

A comparative evaluation of deep learning approaches for ophthalmology.

Scientific reports
There is a growing number of publicly available ophthalmic imaging datasets and open-source code for Machine Learning algorithms. This allows ophthalmic researchers and practitioners to independently perform various deep-learning tasks. With the adva...

Gemini AI vs. ChatGPT: A comprehensive examination alongside ophthalmology residents in medical knowledge.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
INTRODUCTION: The rapid advancement of artificial intelligence (AI), particularly in large language models like ChatGPT and Google's Gemini AI, marks a transformative era in technological innovation. This study explores the potential of AI in ophthal...