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Improving Dietary Supplement Information Retrieval: Development of a Retrieval-Augmented Generation System With Large Language Models.

Journal of medical Internet research
BACKGROUND: Dietary supplements (DSs) are widely used to improve health and nutrition, but challenges related to misinformation, safety, and efficacy persist due to less stringent regulations compared with pharmaceuticals. Accurate and reliable DS in...

Interaction effect between data discretization and data resampling for class-imbalanced medical datasets.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundData discretization is an important preprocessing step in data mining for the transfer of continuous feature values to discrete ones, which allows some specific data mining algorithms to construct more effective models and facilitates the d...

Clinical Application of Artificial Intelligence Preoperative Planning System Combined with Expert Database Retrieval in Complex Revision Hip Surgery.

Journal of visualized experiments : JoVE
Accurate preoperative planning in revision hip arthroplasty is crucial for achieving successful outcomes. To enhance the intuitive evaluation of acetabular bone defect severity and leverage previous successful experience in revision hip arthroplasty,...

Machine learning risk-prediction model for in-hospital mortality in Takotsubo cardiomyopathy.

International journal of cardiology
BACKGROUND: Takotsubo cardiomyopathy (TC) is an acute heart failure syndrome characterized by transient left ventricular dysfunction, often triggered by stress. Data on risk scores predicting mortality in TC is sparse. We developed a machine-learning...

A comprehensive experimental comparison between federated and centralized learning.

Database : the journal of biological databases and curation
Federated learning is an upcoming machine learning paradigm which allows data from multiple sources to be used for training of classifiers without the data leaving the source it originally resides. This can be highly valuable for use cases such as me...

Enhancing skin disease classification leveraging transformer-based deep learning architectures and explainable AI.

Computers in biology and medicine
Skin diseases affect over a third of the global population, yet their impact is often underestimated. Automating the classification of these diseases is essential for supporting timely and accurate diagnoses. This study leverages Vision Transformers,...

SERS-ATB: A comprehensive database server for antibiotic SERS spectral visualization and deep-learning identification.

Environmental pollution (Barking, Essex : 1987)
The rapid and accurate identification of antibiotics in environmental samples is critical for addressing the growing concern of antibiotic pollution, particularly in water sources. Antibiotic contamination poses a significant risk to ecosystems and h...

The impact of training image quality with a novel protocol on artificial intelligence-based LGE-MRI image segmentation for potential atrial fibrillation management.

Computer methods and programs in biomedicine
BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting up to 2 % of the population. Catheter ablation is a promising treatment for AF, particularly for paroxysmal AF patients, but it often has high recurrence rates. Dev...

CACTUS: An open dataset and framework for automated Cardiac Assessment and Classification of Ultrasound images using deep transfer learning.

Computers in biology and medicine
Cardiac ultrasound (US) scanning is one of the most commonly used techniques in cardiology to diagnose the health of the heart and its proper functioning. During a typical US scan, medical professionals take several images of the heart to be classifi...