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 ...
Abstract: As one of the core tasks in vision recognition, image classification is widely used in various scenarios. Most existing mainstream image classification models use the Convolutional Neural ...
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 ...
Abstract: This paper presents a novel sleep/wake classification method based on heart rate and pulse oximetry, using logistic model with derived dynamic time warping and correlation features ...
Background: Early identification of Type 1 Diabetes Mellitus (T1DM) in pediatric populations is crucial for implementing timely interventions and improving long-term outcomes. Peripheral blood ...
Researchers have developed an AI model that uses epigenetic DNA signatures to identify tumors with over 99% accuracy, potentially replacing risky biopsies with safer, faster diagnoses. Credit: ...
When it comes to artificial intelligence, more intensive computing uses more energy, producing more greenhouse gases. By Sachi Kitajima Mulkey Graphics by Harry Stevens From uninvited results at the ...
Logistic regression is the most cost-effective model for medial vascular calcification classification, with a mean ICER of $278 using five low-cost features. Despite similar diagnostic accuracy, ...
Piloting an aircraft is a cognitive task that requires continuous verbal, visual, and auditory attentions (e.g., Air Traffic Control Communication). An increase or decrease in mental workload from a ...
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