This important study reports three experiments examining how the subjective experience of task regularities influences perceptual decision-making. Although the evidence linking subjective ratings to ...

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 ...

A new risk score may identify patients with node-negative pancreatic neuroendocrine tumors who face a high risk for recurrence after surgery.

The authors provide a useful integrated analytical approach to investigating MASLD focused on diverse multiomic integration methods. The strength of evidence for this new resource is solid, as ...

Abstract: E-health sensors and wearables play an important role in the detection and classification of many chronic diseases. A chronic disease requires active monitoring and its severity increases ...

Researchers at örebro University have developed two new AI models that can analyze the brain's electrical activity and accurately distinguish between healthy individuals and patients with dementia, ...

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...

Background Heart auscultation is a widely used and cost-effective clinical tool for detecting valvular heart disease (VHD), particularly in primary care. However, existing evidence on its diagnostic ...

Introduction: In recent years, advancements in machine learning and electronic stethoscope technology have enabled high-precision recording and analysis of lung sounds, significantly enhancing ...

Abstract: Quantum machine learning (QML) presents a promising avenue for addressing complex classification challenges, yet its application in medical imaging remains largely unexplored. This work ...