The diagnosis of glaucoma is still a topic of intense research, considering no diagnostic criteria is currently agreed upon. With the introduction of artificial intelligence (AI) in the medical diagnosis and the approval of dozens of AI-based models to aid in medical diagnosis, it is the hope that these technological advances might aid in the development of a reliable, yet practical criteria or method to diagnose glaucoma. From the use of historical and clinic based data to advanced imaging techniques, AI models might be trained.
The goal of this research topic is to:
Explore how AI improved the diagnostic accuracy of glaucoma
Assess openly accessible datasets for glaucoma diagnosis, their usefulness and accuracy in AI-assisted glaucoma diagnosis
Assess different imaging modalities and their contribution in AI-assisted glaucoma diagnosis
Assess different AI models and their contribution in glaucoma diagnosis
Assess the impact of recent advances in natural language processing (NLP), particularly ChatGPT and advanced language models, in the diagnosis and assessment of glaucoma patients.
Obstacles in developing an AI model for glaucoma diagnosis
Highly relevant articles include those related to the above discussed topics. However, we also welcome research related to advances in glaucoma diagnosis generally, AI use in glaucoma management, or future developments in glaucoma in the context of AI.
It is important to note that the following articles types are considered in this research topic:
Type (A) Articles: Original Research, Systematic Review, Methods, Review, Hypothesis & Theory, Clinical Trial, Classification, Technology and Code, Study Protocol
Type (B) Articles: Mini Review, Perspective, Case Report, Brief Research Report
Type (C) Articles: Data Report, General Commentary, Opinion
The diagnosis of glaucoma is still a topic of intense research, considering no diagnostic criteria is currently agreed upon. With the introduction of artificial intelligence (AI) in the medical diagnosis and the approval of dozens of AI-based models to aid in medical diagnosis, it is the hope that these technological advances might aid in the development of a reliable, yet practical criteria or method to diagnose glaucoma. From the use of historical and clinic based data to advanced imaging techniques, AI models might be trained.
The goal of this research topic is to:
Explore how AI improved the diagnostic accuracy of glaucoma
Assess openly accessible datasets for glaucoma diagnosis, their usefulness and accuracy in AI-assisted glaucoma diagnosis
Assess different imaging modalities and their contribution in AI-assisted glaucoma diagnosis
Assess different AI models and their contribution in glaucoma diagnosis
Assess the impact of recent advances in natural language processing (NLP), particularly ChatGPT and advanced language models, in the diagnosis and assessment of glaucoma patients.
Obstacles in developing an AI model for glaucoma diagnosis
Highly relevant articles include those related to the above discussed topics. However, we also welcome research related to advances in glaucoma diagnosis generally, AI use in glaucoma management, or future developments in glaucoma in the context of AI.
It is important to note that the following articles types are considered in this research topic:
Type (A) Articles: Original Research, Systematic Review, Methods, Review, Hypothesis & Theory, Clinical Trial, Classification, Technology and Code, Study Protocol
Type (B) Articles: Mini Review, Perspective, Case Report, Brief Research Report
Type (C) Articles: Data Report, General Commentary, Opinion
