Opportunities and Challenges of Chatbots in Ophthalmology: A Narrative Review

Journal of Personalized Medicine, Journal Year: 2024, Volume and Issue: 14(12), P. 1165 - 1165

Published: Dec. 21, 2024

Artificial intelligence (AI) is becoming increasingly influential in ophthalmology, particularly through advancements machine learning, deep robotics, neural networks, and natural language processing (NLP). Among these, NLP-based chatbots are the most readily accessible driven by AI-based large models (LLMs). These have facilitated new research avenues gained traction both clinical surgical applications ophthalmology. They also being utilized studies on ophthalmology-related exams, those containing multiple-choice questions (MCQs). This narrative review evaluates opportunities challenges of integrating into ophthalmology research, with separate assessments involving open- close-ended questions. While demonstrated sufficient accuracy handling MCQ-based studies, supporting their use education, additional exam security measures necessary. The open-ended question responses suggests that LLM could be applied across nearly all areas shown promise for addressing patient inquiries, offering medical advice, triage, facilitating diagnosis differential diagnosis, aiding planning. However, ethical implications, confidentiality concerns, physician liability, issues surrounding privacy remain pressing challenges. Although AI has significant care, it currently effective as a supportive tool rather than replacement human physicians.

Language: Английский

Artificial intelligence derived large language model in decision-making process in uveitis

International Journal of Retina and Vitreous, Journal Year: 2024, Volume and Issue: 10(1)

Published: Sept. 11, 2024

Language: Английский

Exploring the Role of Large Language Models in Melanoma: A Systematic Review

Journal of Clinical Medicine, Journal Year: 2024, Volume and Issue: 13(23), P. 7480 - 7480

Published: Dec. 9, 2024

: This systematic review evaluates the current applications, advantages, and challenges of large language models (LLMs) in melanoma care.

Language: Английский