AIMC Topic: Large Language Models

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The impact of the large language model ChatGPT in oral and maxillofacial surgery: a systematic review.

The British journal of oral & maxillofacial surgery
This systematic review evaluates the impact of the large language model (LLM) ChatGPT in oral and maxillofacial surgery. Following PRISMA guidelines and registered in PROSPERO (CRD42024625882), the study involved a comprehensive search across PubMed/...

Detecting emergencies in patient portal messages using large language models and knowledge graph-based retrieval-augmented generation.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: This study aims to develop and evaluate an approach using large language models (LLMs) and a knowledge graph to triage patient messages that need emergency care. The goal is to notify patients when their messages indicate an emergency, gu...

AI driven cardiovascular risk prediction using NLP and Large Language Models for personalized medicine in athletes.

SLAS technology
The performance and long-term health of athletes are significantly influenced by their cardiovascular resilience and associated risk factors. This study explores the innovative applications of Natural Language Processing (NLP) and Large Language Mode...

Large language models in breast cancer reconstruction: A framework for patient-specific recovery and predictive insights.

SLAS technology
Breast cancer reconstruction, a vital part of comprehensive cancer therapy, can be performed concurrently with cancer resection, improving both physical and psychological recovery for patients. However, the intricacy and variety of recovery demand a ...

Integrating large language models with human expertise for disease detection in electronic health records.

Computers in biology and medicine
OBJECTIVE: Electronic health records (EHR) are widely available to complement administrative data-based disease surveillance and healthcare performance evaluation. Defining conditions from EHR is labour-intensive and requires extensive manual labelli...

Domain-specific language models: innovation with inherent risks.

Revista espanola de enfermedades digestivas
There are potential advantages of domain-specific solutions, built by fine-tuning pretrained LLMs with healthcare data, but this approach has certain drawbacks: privacy, biases and accuracy.

Evaluating the effectiveness of biomedical fine-tuning for large language models on clinical tasks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Large language models (LLMs) have shown potential in biomedical applications, leading to efforts to fine-tune them on domain-specific data. However, the effectiveness of this approach remains unclear. This study aims to critically evaluat...

The Large Language Models on Biomedical Data Analysis: A Survey.

IEEE journal of biomedical and health informatics
With the rapid development of Large Language Model (LLM) technology, it has become an indispensable force in biomedical data analysis research. However, biomedical researchers currently have limited knowledge about LLM. Therefore, there is an urgent ...

User Intent to Use DeepSeek for Health Care Purposes and Their Trust in the Large Language Model: Multinational Survey Study.

JMIR human factors
BACKGROUND: Generative artificial intelligence (AI)-particularly large language models (LLMs)-has generated unprecedented interest in applications ranging from everyday questions and answers to health-related inquiries. However, little is known about...

Dual retrieving and ranking medical large language model with retrieval augmented generation.

Scientific reports
Recent advancements in large language models (LLMs) have significantly enhanced text generation across various sectors; however, their medical application faces critical challenges regarding both accuracy and real-time responsiveness. To address thes...