Latest AI and machine learning research in devices and vaccines for healthcare professionals.
BACKGROUND: In contemporary dental practice, implants are the standard solution for edentulism. However, the wide variety of implant brands and the prevalence of peri-implantitis present significant diagnostic hurdles for clinicians. This study evaluated an automated hybrid AI framework designed to simultaneously identify implant brands, determine clinical treatment stages, and classify peri-impla...
BACKGROUND: Transformer-based architectures have rapidly gained prominence in medical imaging due to their ability to model long-range dependencies and global contextual information more effectively than convolutional neural networks. In dentistry, their applications have expanded across diagnostic, predictive, and generative tasks, yet no comprehensive synthesis has systematically evaluated their...
BACKGROUND: Lung cancer ranks among the most lethal malignancies globally, and its traditional diagnosis suffers from strong subjectivity, high misdia...
AIM: Machine learning (ML) applications in pharmacovigilance remain limited and underexplored. Using data from the French National pharmacovigilance d...
Accurately detecting patterns of interest across a large number of images presents a significant challenge in data analysis for high-throughput analyt...
In recent years, metal-organic frameworks (MOFs) have emerged as highly promising materials for advanced gas sensing owing to their tunable pore struc...
OBJECTIVE: To systematically characterise United States Food and Drug Administration (FDA) authorised urology-specific artificial intelligence (AI)-en...
PURPOSE: This narrative review aims to systematically summarize and compile available evidence on the applications of artificial intelligence (AI) acr...
BACKGROUND: Heart failure (HF) is a leading cause of hospitalization and readmission. Cardiac implantable electronic devices (CIEDs) continuously capt...
OBJECTIVE: In this study, we describe a deep learning framework for automated seizure annotation in stereo electroencephalography (SEEG) data of patie...
This study employs an integrated computational approach to investigate Mpox vaccine intention in Bangladesh as Mpox immunisation strategies require a ...
» Artificial intelligence (AI) is increasingly integrated across the total hip and knee arthroplasty care continuum, including preoperative risk strat...
BACKGROUND: Large language models (LLMs) are used for clinical information retrieval, yet their performance on highly domain-specific documents such a...
While multispectral sensors offer a cost-effective and robust solution for monitoring plant responses to environmental stress, their limited spectral ...
The U.S. FDA classifies food recalls into three severity tiers (Class IÂ /Â IIÂ /Â III), a decision that drives public notification urgency and regulatory...
INTRODUCTION: Highly attenuated poxviruses serve as potent viral vectors, oncolytic agents, and therapeutic vaccines. They can accommodate and stably ...
BACKGROUND: Accurate clinical outcome prediction using electronic health records (EHRs) is crucial for patient care and resource allocation. EHRs incl...
BACKGROUND: Breast implant surgery is a high-volume procedure, yet predicting device-related complications that require revision surgery remains chall...
BACKGROUND: Artificial intelligence (AI)-enabled software is increasingly integrated into digital and computational pathology, driving new regulatory ...