Maxwell Singer

Removal notice to “Development and Evaluation of Aeyeconsult: A Novel Ophthalmology Chatbot Leveraging Verified Textbook Knowledge and GPT-4” [Journal of Surgical Education 81 (2024) 438]

Maxwell Singer, Julia J. Fu, Jessica Chow, Christopher C. Teng

us (code pays fourni par la source)

Rethinking Retrieval-Augmented Generation for Medicine: A Large-Scale, Systematic Expert Evaluation and Practical Insights

Hyunjae Kim, Jiwoong Sohn, Aidan Gilson, Nicholas Cochran-Caggiano et autres

Large language models (LLMs) are transforming the landscape of medicine, yet two fundamental challenges persist: keeping up with rapidly evolving medical knowledge and providing verifiable, evidence-grounded reasoning. Retrieval-augmented generation (RAG) has been widely adopted to address these limitations by supplementing model outputs …

Ophthalmological Question Answering and Reasoning Using OpenAI o1 vs Other Large Language Models

Sahana Srinivasan, X. C. Ai, Minjie Zou, Ke Zou et autres

Importance: OpenAI's recent large language model (LLM) o1 has dedicated reasoning capabilities, but it remains untested in specialized medical fields like ophthalmology. Evaluating o1 in ophthalmology is crucial to determine whether its general reasoning can meet specialized needs or if domain-specific LLMs …

sg, us, cn, ca (code pays fourni par la source)

BEnchmarking LLMs for Ophthalmology (BELO) for Ophthalmological Knowledge and Reasoning

Sahana Srinivasan, X. C. Ai, Thaddaeus Wai Soon Lo, Aidan Gilson et autres

Current benchmarks evaluating large language models (LLMs) in ophthalmology are limited in scope and disproportionately prioritise accuracy. We introduce BELO (BEnchmarking LLMs for Ophthalmology), a standardized and comprehensive evaluation benchmark developed through multiple rounds of expert checking by 13 ophthalmologists. BELO assesses …

Benchmarking Next-Generation Reasoning-Focused Large Language Models in Ophthalmology: A Head-to-Head Evaluation on 5,888 Items

Minjie Zou, Sahana Srinivasan, Thaddaeus Wai Soon Lo, Ke Zou et autres

Recent advances in reasoning-focused large language models (LLMs) mark a shift from general LLMs toward models designed for complex decision-making, a crucial aspect in medicine. However, their performance in specialized domains like ophthalmology remains underexplored. This study comprehensively evaluated and compared the …

Benchmarking large language models for biomedical natural language processing applications and recommendations

Qingyu Chen, Yan Hu, Xueqing Peng, Qianqian Xie et autres

The rapid growth of biomedical literature poses challenges for manual knowledge curation and synthesis. Biomedical Natural Language Processing (BioNLP) automates the process. While Large Language Models (LLMs) have shown promise in general domains, their effectiveness in BioNLP tasks remains unclear due to …

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Retinal and Optic Nerve Lesions Correspond to Amyloid in Autosomal Dominant Alzheimer’s Disease

Amir H. Kashani, Maya Koronyo‐Hamaoui, Yosef Koronyo, Haoshen Shi et autres

Abstract Autosomal dominant Alzheimer’s disease (ADAD) is a rare form of Alzheimer’s disease (AD) in which the biology of the disease can be explored during the presymptomatic phase of the illness. The retina is an outgrowth of the central nervous system and …

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Can OpenAI o1 Reason Well in Ophthalmology? A 6,990-Question Head-to-Head Evaluation Study

Sahana Srinivasan, X. C. Ai, Minjie Zou, Ke Zou et autres

Question: What is the performance and reasoning ability of OpenAI o1 compared to other large language models in addressing ophthalmology-specific questions? Findings: This study evaluated OpenAI o1 and five LLMs using 6,990 ophthalmological questions from MedMCQA. O1 achieved the highest accuracy (0.88) …

Can OpenAI o1's Enhanced Reasoning Capabilities Extend to Ophthalmology? A Benchmark Study Across Large Language Models and Text Generation Metrics

Sahana Srinivasan, X. C. Ai, Minjie Zou, Ke Zou et autres

sg, us (code pays fourni par la source)

LEME: Open Large Language Models for Ophthalmology with Advanced Reasoning and Clinical Validation

Hyunjae Kim, X. C. Ai, Sahana Srinivasan, Aidan Gilson et autres

The rising prevalence of eye diseases poses a growing public health burden. Large language models (LLMs) offer a promising path to reduce documentation workload and support clinical decision-making. However, few have been tailored for ophthalmology, and most evaluations focus mainly on knowledge-based …

Enhancing Large Language Models with Domain-specific Retrieval Augment Generation: A Case Study on Long-form Consumer Health Question Answering in Ophthalmology

Aidan Gilson, X. C. Ai, Thilaka Arunachalam, Ki Xiong Cheong et autres

Despite the potential of Large Language Models (LLMs) in medicine, they may generate responses lacking supporting evidence or based on hallucinated evidence. While Retrieval Augment Generation (RAG) is popular to address this issue, few studies implemented and evaluated RAG in downstream domain-specific …

Retinal Ischemic Perivascular Lesions Are Associated With Stroke in Individuals With Atrial Fibrillation

Christine Y. Bakhoum, Adrian Au, Elodie Bousquet, Mitchelle Matesva et autres

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