We propose a geometric deep-learning-based framework, TractGeoNet, for performing
regression using diffusion magnetic resonance imaging (dMRI) tractography and associated …

Predicting socioeconomic indicators from satellite imagery with deep learning has become
an increasingly popular research direction. Post-hoc concept-based explanations can be an …

Remaining useful life (RUL) prediction is of vital significance in prognostics health
management tasks. Due to powerful learning capabilities, deep learning methods …

Accurate state of health (SOH) estimation is basis for safe and reliable operation of lithium-
ion batteries. In practice, accurate and reliable SOH estimation remains a challenge due to …

Whole-body fatigue (WBF) presents a concerning risk to construction workers, which can
impact function and ultimately lead to accidents and diminished productivity. This study …

Deep learning methodologies employed for biomass prediction often neglect the intricate
relationships between labels and samples, resulting in suboptimal predictive performance …

Exercise-based rehabilitation programs have proven to be effective in enhancing the quality
of life and reducing mortality and rehospitalization rates. AI-driven virtual rehabilitation …

In the field of neuroimaging, accurate brain age prediction is pivotal for uncovering the
complexities of brain aging and pinpointing early indicators of neurodegenerative …

Regression is a fundamental task in machine learning that has garnered extensive attention
over the past decades. The conventional approach for regression involves employing loss …

Deep learning (DL) models have been advancing automatic medical image analysis on
various modalities, including echocardiography, by offering a comprehensive end-to-end …