Parkinson's disease (PD) is a complex neurodegenerative disease in the elderly. This
disease has no cure, but assessing these motor symptoms will help slow down that …

Multi-task learning with temporal relation is a common prediction method for modelling the
evolution of a wide range of systems. Considering the inherent relations between multiple …

In the rapidly evolving field of neuroinformatics, the intersection of artificial intelligence (AI)
and neuroscience presents both unprecedented opportunities and formidable ethical …

In this paper, we propose a novel efficient multi-task learning formulation for the class of
progression problems in which its state will continuously change over time. To use the …

Identifying and utilising various biomarkers for tracking Alzheimer's disease (AD)
progression have received many recent attentions and enable helping clinicians make the …

Precision fertilization is essential in agricultural systems for balancing soil nutrients,
conserving fertilizer, decreasing emissions, and increasing crop yields. Access to …

Recently, there have been a wide spectrum of multitask learning (MTL) methods developed
to model Alzheimer's disease (AD) progression. Typical MTL studies related cognitive ability …

Multi-task learning methods have been studied in Alzheimer's disease for cognitive status
prediction and neuroimaging feature identification widely by utilizing prior constraints …

Multi-task feature learning (MTFL) methods play a key role in predicting Alzheimer's disease
(AD) progression. These studies adhere to a unified feature-sharing framework to promote …