Reverse Logistics, Artificial Intelligence, Circular Economy, Supply Chain Management, Sustainability, Machine Learning Share and Cite: Waditwar, P. (2026) De-Risking Returns: How AI Can Reinvent Big ...
Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...
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 ...
Discover the leading robotic process automation tools for enterprises in 2025 that enhance digital transformation, reduce costs, and increase efficiency. Learn about RPA software features and pricing ...
Researchers from Skoltech Engineering Center's Hierarchically Structured Materials Laboratory have developed a new method to ...
Abstract: Feature extraction and selection in the presence of nonlinear dependencies among the data is a fundamental challenge in unsupervised learning. We propose using a Gram-Schmidt (GS) type ...
This issue of The Journal of Risk Model Validation features two papers that directly address validation using machine learning. Whether their findings imply we will all (including the editor) become ...
Dementia is a group of disorders that gradually impair memory, thinking and daily functioning. Alzheimer's disease (AD), the ...
The researchers also argue that explainable AI models are essential for ensuring fairness and accountability in policy design. In traditional statistical models, the relationships between variables ...
From 11.5 million alloy candidates to AI-guided perovskites, this piece unpacks how materials informatics is speeding up discovery, design, and deployment in engineering.
Dementia, including Alzheimer’s (AD) and frontotemporal dementia (FTD), often causes overlapping symptoms, making diagnosis challenging. Traditional imaging is costly and slow, while EEG offers a ...
The Punch on MSN
At the intersection of AI, engineering, and human learning
Taiwo Feyijimi stands at a rare crossroads where advanced artificial intelligence, engineering education, and human learning converge. As a doctoral candidate in Engineering Education Transformations ...
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