Journal of the World federation of orthodontists
Jan 17, 2026
OBJECTIVE: Precise identification of tooth and gingival boundaries in digital models is essential for effective orthodontic diagnosis, treatment planning, and appliance fabrication. Recent advances in artificial intelligence (AI) offer opportunities ... read more
BACKGROUND: Machine learning prediction models require prospective validation to ensure implementation fidelity and feasibility. Our primary objective was to prospectively validate a previously reported postoperative mortality prediction model in inp... read more
Left bundle branch block (LBBB) is an important electrocardiographic (ECG) finding strongly associated with left ventricular systolic dysfunction (LVSD), a condition linked to poor clinical outcomes. Although early LVSD detection is crucial, standard... read more
BACKGROUND: Adenoid hypertrophy is a common cause of pediatric obstructive sleep apnea (OSA), which can impair cognitive development and affect craniofacial development. Given that adenoids typically regress with age and may respond to oral appliance... read more
BACKGROUND: Accurate individual risk assessment is crucial for guiding and improving the prevention of atherosclerotic cardiovascular disease (ASCVD). Existing prediction models are primarily derived from Western Caucasian and Chinese Han populations... read more
BACKGROUND: There has been a notable increase in artificial intelligence (AI) studies in dentistry. However, the inadequate use of proper validation methods has led to overly optimistic performance metrics of machine learning (ML) models. External va... read more
Extracellular vesicles (EVs) are emerging as naturally bioactive nanomaterials with intrinsic biocompatibility and targeting potential. Recent integration of machine learning (ML) into EV research has accelerated advances in molecular profiling, stru... read more
Medical science monitor : international medical journal of experimental and clinical research
Jan 17, 2026
BACKGROUND We suggest that testing a large language model (LLM) chatbot in terms of the accuracy of the references it provides could be a powerful, quantifiable means of rating its inherent degree of misinformation, since the accuracy of the bibliogr... read more
PURPOSE: To evaluate the proposed explainable denoising deep learning model, Grouped Shared Convolutional Attention Vision Transformer (GSCAViT), for classifying normal fetal echocardiogram. METHODS: A retrospective study was conducted on 358 fetal c... read more
Metabolic dysfunction-associated steatohepatitis (MASH) is a global health care burden. Appropriate large animal models mimicking the main MASH characteristics of steatosis, inflammation, and hepatocyte damage alongside progression of fibrosis are im... read more
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