BACKGROUND: Sepsis poses a significant threat in emergency settings, necessitating tools for early and interpretable risk assessment. This study aimed to develop a robust explainable boosting machine (EBM) model, one of the explainable artificial int...
Text-to-image (T2I) artificial intelligence models are being increasingly explored in medical education, yet their utility in ophthalmology remains unclear. Slit-lamp anterior segment photography, as a cornerstone of ophthalmic training, provides an ...
OBJECTIVE: To develop and validate a 10-year predictive model for cardiovascular and metabolic disease (CVMD) risk using comprehensive health examination data from nearly 37 701 individuals.
Journal of the American Society for Mass Spectrometry
Nov 27, 2025
Proteogenomics integrates genomics and mass spectrometry (MS) data to understand complex biological systems, disease mechanisms, and potential biomarkers. However, the high volume and noise in MS data present computational and interpretational challe...
BACKGROUND: The application of deep learning techniques in cephalometric analysis has become increasingly prominent. Although automatic landmarking models for cephalometric analysis have been developed, their accuracy still requires validation and re...
This study aimed to determine the optimized scan time and injected activity regimen for clinical Ga DOTATATE PET/CT in neuroendocrine tumor imaging through an experimental approach without using machine learning techniques.A NEMA PET body phantom was...
BACKGROUND: Coronary computed tomography angiography (CCTA) is widely used as a first-line tool for diagnosing and managing coronary artery disease (CAD), and machine learning (ML)-based analysis shows promise for quantitative CAD assessment.
UNLABELLED: This article aims to evaluate the quality of responses provided by AI systems ChatGPT-4o and Gemini 1.5 to frequently asked patient questions regarding pectus deformity.
This study investigates how personality traits, specifically those measured by the HEXACO Personality Inventory and the Dark Triad, predict university students' attitudes toward generative artificial intelligence (GAI) and their engagement in GAI-rel...
OBJECTIVES: Inappropriately treated pain can have deleterious outcomes in infants. Current tools rely on intermittent, subjective observation requiring specialised paediatric skills. This study aimed to diagnose infant pain through continuous monitor...
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