AIMC Topic: Large Language Models

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Transforming breast cancer diagnosis and treatment with large language Models: A comprehensive survey.

Methods (San Diego, Calif.)
Breast cancer (BrCa), being one of the most prevalent forms of cancer in women, poses many challenges in the field of treatment and diagnosis due to its complex biological mechanisms. Early and accurate diagnosis plays a fundamental role in improving...

A Systemic Review of Large Language Models and Their Implications in Dermatology.

The Australasian journal of dermatology
In computational linguistics, large language models have reached a significant turning point. They have quickly spread throughout several sectors, including the medical field. By integrating demographics, clinical photos, medical interviews, or genet...

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

Nature communications
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, t...

AI as a decision support tool in forensic image analysis: A pilot study on integrating large language models into crime scene investigation workflows.

Journal of forensic sciences
This study evaluates the effectiveness of artificial intelligence (AI) tools (ChatGPT-4, Claude, and Gemini) in forensic image analysis of crime scenes, marking a significant step toward developing bespoke AI models for forensic applications. The res...

Virtual Patients Using Large Language Models: Scalable, Contextualized Simulation of Clinician-Patient Dialogue With Feedback.

Journal of medical Internet research
BACKGROUND: Virtual patients (VPs) are computer screen-based simulations of patient-clinician encounters. VP use is limited by cost and low scalability.

Estimating depression severity in narrative clinical notes using large language models.

Journal of affective disorders
BACKGROUND: Depression treatment guidelines emphasize measurement-based care using patient-reported outcome measures, yet their impact on narrative documentation quality remains underexplored.

Comparing large Language models and human annotators in latent content analysis of sentiment, political leaning, emotional intensity and sarcasm.

Scientific reports
In the era of rapid digital communication, vast amounts of textual data are generated daily, demanding efficient methods for latent content analysis to extract meaningful insights. Large Language Models (LLMs) offer potential for automating this proc...

Large Language Models in Summarizing Radiology Report Impressions for Lung Cancer in Chinese: Evaluation Study.

Journal of medical Internet research
BACKGROUND: Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities in various natural language processing tasks, particularly in text generation. However, their effectiveness in summarizing radiology report impressio...

Amyloid-β Deposition Prediction With Large Language Model Driven and Task-Oriented Learning of Brain Functional Networks.

IEEE transactions on medical imaging
Amyloid- positron emission tomography can reflect the Amyloid- protein deposition in the brain and thus serves as one of the golden standards for Alzheimer's disease (AD) diagnosis. However, its practical cost and high radioactivity hinder its applic...

Personalized glucose forecasting for people with type 1 diabetes using large language models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Type 1 Diabetes (T1D) is an autoimmune disease that requires exogenous insulin via Multiple Daily Injections (MDIs) or subcutaneous pumps to maintain targeted glucose levels. Despite the advances in Continuous Glucose Monito...