AI revolutionises sleep disorder diagnosis: IIITH leads breakthroughs

Hyderabad: Artificial Intelligence (AI) is transforming the way sleep disorders are diagnosed, with researchers at the ...
Scientific Research Publishing

Early Alzheimer’s Disease Detection from Short Speech Samples Using Lightweight, Interpretable Linguistic Markers ()

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 ...

Automatic label checking: The missing step in making medical AI reliable

Researchers at Osaka Metropolitan University have discovered a practical way to detect and fix common labeling errors in ...
News-Medical.Net

Automated system improves deep learning accuracy in chest radiography analysis

Researchers at Osaka Metropolitan University have discovered a practical way to detect and fix common labeling errors in ...
Scientific Research Publishing

Multimodal Digital Phenotyping for Bipolar Disorder: Robust Mood-State Classification and Early Relapse Risk Monitoring ()

Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

In large public multi-site fMRI datasets, the sample characteristics, data acquisition methods, and MRI scanner models vary across sites and datasets. This non-neural variability obscures neural ...
Frontiers

BrainTumNet: multi-task deep learning framework for brain tumor segmentation and classification using adaptive masked transformers

Background and objective: Accurate diagnosis of brain tumors significantly impacts patient prognosis and treatment planning. Traditional diagnostic methods primarily rely on clinicians’ subjective ...
IEEE

Partial Multi-View Incomplete Multi-Label Learning Network With Quality-Aware Representation Fusion

Abstract: Recently, the topic of multi-view multi-label classification has aroused significant attention from scholars. Plenty of methods adopt an average weighting scheme to merge the features ...