Artificial intelligence (AI) is rife with optimization problems, from automating feature engineering and hyperparameter tuning to training intricate neural networks. Finding a balance between exploration and exploitation remains a significant challen... read more
Aquatic environments are key reservoirs and dissemination pathways of antimicrobial resistance (AMR). However, current water-based surveillance remains fragmented and inefficient for the timely detection of emerging threats. Integrating artificial in... read more
BACKGROUND AND AIMS: Early detection of chronic kidney disease (CKD) in high-altitude regions remains difficult due to physiological adaptations that may affect conventional biomarkers. This study aimed to develop machine learning-based diagnostic mo... read more
BACKGROUND: Magnetic resonance imaging (MRI) of breast tissue is often used to definitively diagnose breast cancer due to its high soft-tissue contrast. However, its high cost and limited accessibility make it unsuitable for real-time screening, unli... read more
Machine Learning (ML) and Artificial Intelligence (AI) approaches have potential to make better-informed decisions in chemical hazard identification while reducing animal testing. Their application in the context of New Approach Methodologies (NAMs) ... read more
BACKGROUND: Parkinson's Disease (PD) is a neuro-degenerative condition that progressively impairs movement, resulting from the loss of dopamine-producing brain cells. Early detection of such a condition helps slowing their progression and allows more... read more
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