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) ...
IEEE

T3SSLNet: Triple-Method Self-Supervised Learning for Enhanced Brain Tumor Classification in MRI

Abstract: Classification of brain tumors from MRI images is crucial for early diagnosis and effective treatment planning. However, there are still obstacles to overcome, including low image quality, ...
Frontiers

A dynamic multitask evolutionary algorithm for high-dimensional feature selection based on multi-indicator task construction and elite competition learning

High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...
Digital Trends

Perplexity AI turns into tutor with new language learning feature

What’s happened? Perplexity AI just dropped a new language learning feature built right into its platform. In a post shared on social media, the company announced a tool that helps users learn by ...
Frontiers

Advanced Supervised Machine Learning Techniques for Accurate Prediction of Diabetes Mellitus Using Feature Selection

The final, formatted version of the article will be published soon. Background): Diabetes Mellitus (DM) is a chronic metabolic disorder that poses a significant global health challenge, affecting ...
IEEE

MGL-FBLS: Multi-Granularity Label-Driven Feature Enhanced Broad Learning System for Semi-Supervised Classification

Abstract: The Broad Learning System (BLS) performs well in semi-supervised scenarios across many datasets, but its effectiveness is often limited by inadequate feature extraction and inefficient label ...