Artificial intelligence brings to classification a scalable, accurate alternative. Using natural language processing and ...

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 ...

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 ...

Study: Artificial intelligence model as a tool to predict prediabetes. Image Credit: CI Photos / Shutterstock In a recent study published in the journal Scientific Reports, researchers developed a ...

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 ...

Introduction The UN General Assembly in 2018 passed a resolution to eliminate obstetric fistula within a decade. Because the ...

AI chatbot achieves high accuracy in performing clinical patient diagnostic interviews for common mental health disorders.

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

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

The progression of glaucoma was accurately predicted by machine learning models based on structural, functional and vascular ...

Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...