AIMC Topic: Large Language Models

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BiomedRAG: A retrieval augmented large language model for biomedicine.

Journal of biomedical informatics
Retrieval-augmented generation (RAG) involves a solution by retrieving knowledge from an established database to enhance the performance of large language models (LLM). , these models retrieve information at the sentence or paragraph level, potential...

Factors Associated With the Accuracy of Large Language Models in Basic Medical Science Examinations: Cross-Sectional Study.

JMIR medical education
BACKGROUND: Artificial intelligence (AI) has become widely applied across many fields, including medical education. Content validation and its answers are based on training datasets and the optimization of each model. The accuracy of large language m...

Patient- and clinician-based evaluation of large language models for patient education in prostate cancer radiotherapy.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
BACKGROUND: This study aims to evaluate the capabilities and limitations of large language models (LLMs) for providing patient education for men undergoing radiotherapy for localized prostate cancer, incorporating assessments from both clinicians and...

Open-source Large Language Models can Generate Labels from Radiology Reports for Training Convolutional Neural Networks.

Academic radiology
RATIONALE AND OBJECTIVES: Training Convolutional Neural Networks (CNN) requires large datasets with labeled data, which can be very labor-intensive to prepare. Radiology reports contain a lot of potentially useful information for such tasks. However,...

Leveraging Large Language Models in Radiology Research: A Comprehensive User Guide.

Academic radiology
Large Language Models (LLMs) such as ChatGPT have been increasingly integrated into radiology research, revolutionizing the research landscape. The Radiology Research Alliance (RRA) of the Association for Academic Radiology (AAR) has convened a Task ...

Investigating the role of large language models on questions about refractive surgery.

International journal of medical informatics
BACKGROUND: Large language models (LLMs) are becoming increasingly popular and are playing an important role in providing accurate clinical information to both patients and physicians. This study aimed to investigate the effectiveness of ChatGPT-4.0,...

Facilitators and Barriers of Large Language Model Adoption Among Nursing Students: A Qualitative Descriptive Study.

Journal of advanced nursing
AIM: To explore nursing students' perceptions and experiences of using large language models and identify the facilitators and barriers by applying the Theory of Planned Behaviour.

Large language models for accurate disease detection in electronic health records: the examples of crystal arthropathies.

RMD open
OBJECTIVES: We propose and test a framework to detect disease diagnosis using a recent large language model (LLM), Meta's Llama-3-8B, on French-language electronic health record (EHR) documents. Specifically, it focuses on detecting gout ('goutte' in...

Benchmarking the performance of large language models in uveitis: a comparative analysis of ChatGPT-3.5, ChatGPT-4.0, Google Gemini, and Anthropic Claude3.

Eye (London, England)
BACKGROUND/OBJECTIVE: This study aimed to evaluate the accuracy, comprehensiveness, and readability of responses generated by various Large Language Models (LLMs) (ChatGPT-3.5, Gemini, Claude 3, and GPT-4.0) in the clinical context of uveitis, utiliz...

Large language models can accurately populate Vascular Quality Initiative procedural databases using narrative operative reports.

Journal of vascular surgery
OBJECTIVE: Participation in the Vascular Quality Initiative (VQI) provides important resources to surgeons, but the ability to do so is often limited by time and data entry personnel. Large language models (LLMs) such as ChatGPT (OpenAI) are examples...