AIMC Topic: Large Language Models

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Enhancing data quality in medical concept normalization through large language models.

Journal of biomedical informatics
OBJECTIVE: Medical concept normalization (MCN) aims to map informal medical terms to formal medical concepts, a critical task in building machine learning systems for medical applications. However, most existing studies on MCN primarily focus on mode...

DALL-M: Context-aware clinical data augmentation with large language models.

Computers in biology and medicine
X-ray images are vital in medical diagnostics, but their effectiveness is limited without clinical context. Radiologists often find chest X-rays insufficient for diagnosing underlying diseases, necessitating the integration of structured clinical fea...

Semantic Clinical Artificial Intelligence vs Native Large Language Model Performance on the USMLE.

JAMA network open
IMPORTANCE: Large language models (LLMs) are being implemented in health care. Enhanced accuracy and methods to maintain accuracy over time are needed to maximize LLM benefits.

Adoption of Large Language Model AI Tools in Everyday Tasks: Multisite Cross-Sectional Qualitative Study of Chinese Hospital Administrators.

Journal of medical Internet research
BACKGROUND: Large language model (LLM) artificial intelligence (AI) tools have the potential to streamline health care administration by enhancing efficiency in document drafting, resource allocation, and communication tasks. Despite this potential, ...

Prevalence of Words and Phrases Associated With Large Language Model-Generated Text in the Nursing Literature.

Computers, informatics, nursing : CIN
All disciplines, including nursing, may be experiencing significant changes with the advent of free, publicly available generative artificial intelligence tools. Recent research has shown the difficulty in distinguishing artificial intelligence-gener...

Evaluating a large language model's accuracy in chest X-ray interpretation for acute thoracic conditions.

The American journal of emergency medicine
BACKGROUND: The rapid advancement of artificial intelligence (AI) has great ability to impact healthcare. Chest X-rays are essential for diagnosing acute thoracic conditions in the emergency department (ED), but interpretation delays due to radiologi...

The use of AI large language models by university students for assignment preparation.

Advances in physiology education
Using an opportunity where students were explicitly permitted to use artificial intelligence (AI) applications to prepare an assignment, we compared the practices and beliefs of two distinct student cohorts: second-year science students at a large me...

Reasoning-Driven Food Energy Estimation via Multimodal Large Language Models.

Nutrients
Image-based food energy estimation is essential for user-friendly food tracking applications, enabling individuals to monitor their dietary intake through smartphones or AR devices. However, existing deep learning approaches struggle to recognize a ...

Population Health in Neurology and the Transformative Promise of Artificial Intelligence and Large Language Models.

Seminars in neurology
This manuscript examines the expanding role of population health strategies in neurology, emphasizing systemic approaches that address neurological health at a community-wide level. Key themes include interdisciplinary training in public health, poli...

Integrating machine learning and a large language model to construct a domain knowledge graph for reducing the risk of fall-from-height accidents.

Accident; analysis and prevention
Fall-from-height (FFH) accidents remain a major source of workplace injuries and fatalities. Fall protection systems (FPS) are critical for preventing falls in the work-at-height (WAH) environment. However, challenges in designing and selecting effec...