Predicting high-fidelity ground motions for future earthquakes is crucial for seismic hazard assessment and infrastructure resilience. Conventional empirical simulations suffer from sparse sensor distribution and geographically localized earthquake l... read more
Lumbar spine disorders represent a significant public health concern, with accurate diagnosis relying on vertebral segmentation and quantification. Traditional methods, such as Cobb angle measurement are constrained by two-dimensional projections, wh... read more
Prostate MRI segmentation is critical for accurate diagnosis and treatment planning but remains challenging due to the complex interplay between the peripheral zone's thin, irregular boundaries and the central gland's homogeneous textures, compounded... read more
Although UNet has proven its success in various tasks involving medical image segmentation, its capacity to capture global context is restricted by the finite receptive field inherent to convolutional operations. Transformer is capable of capturing l... read more
A crucial factor for smart cities, which are more vulnerable to cyber threats, is Cyber Resilience (CR). Nevertheless, the conventional frameworks didn't concentrate on assuring the Backup Data (BD) integrity before restoration, showing less resilien... read more
Accurate prediction of bio-oil yield from pyrolysis of organic solid waste is still the main problem in the field of biomass valorization, mostly because of high variability in the composition and the heterogeneity of experimental conditions reported... read more
International journal of obesity (2005)
Mar 16, 2026
BACKGROUND/OBJECTIVES: This study aimed to predict body mass index (BMI) trajectories from childhood to early adulthood using explainable artificial intelligence, integrating adult BMI polygenic scores (PGS), maternal, early-life, and familial factor... read more
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