Biologists mapping the human microbiome expected to find new bacteria and viruses, not entities that slip through every ...

Abstract: Class imbalance occurs frequently in machine learning, particularly in binary classification tasks where the majority class has a significantly larger number of samples than the minority ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...

Dietary assessment has long been a bottleneck in nutrition research and public health. Common tools such as food frequency questionnaires, 24-hour recalls, and weighed food records rely heavily on ...

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 ...

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) ...

Scientists organize millions of proteins by shape, as predicted by AI, revealing 700,000 new families and some shapes unique to humans.

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

The Common Data Set can help prospective students know how much aid they could get to pay for college. Why don’t all schools provide it? By Ron Lieber A similar version of this column was published ...

Abstract: The widespread use of cryptographic protocols such as Transport Layer Security (TLS) has necessitated the development of effective methods for encrypted traffic classification. The existing ...