In a study conducted at the University of Helsinki, AI was trained to classify bird sounds with increasing accuracy. The ...

Mount Sinai analysis looks at the effectiveness of electrocardiograms analyzed via deep learning as a tool for early COPD detection ...

Review re-maps multi-view learning into four supervised scenarios and three granular sub-tiers, delivering the first unified ...

DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification ...

Background/Aims On 17 September 2024, over 3000 pager devices containing explosives were remotely detonated across Lebanon in ...

Abstract: Hyperspectral remote sensing images exhibit high dimensionality, a large volume of data, and significant redundant information. Before using deep learning methods for ground monitoring and ...

Objective This study aimed to evaluate the prevalence and predictors of cardiovascular disease (CVD), chronic kidney disease ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

The handling of missing data in cognitive diagnostic assessment is an important issue. The Random Forest Threshold Imputation (RFTI) method proposed by You et al. in 2023 is specifically designed for ...

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Abstract: We proposes a category imbalance classification model based on mixed feature enhancement between virtual and real domains to address the class imbalance problem in maritime target ...