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 ...
PhD graduates in analytical sciences can leverage transferable skills for careers in regulation, publishing, and startups, beyond traditional academia and R&D. Women in chromatography emphasize the ...
Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...
Feature engineering transforms raw data into the specific inputs that machine learning models need to make accurate predictions. Learn how this crucial process can make the difference between a ...
Abstract: In modern healthcare, predicting diseases and identifying their underlying causes are crucial areas of study. This paper proposes a novel feature selection method based on entropy scores and ...
Abstract: The increasing penetration of inverter-based distributed generation (DG) into power grids improves access to electricity and provides a significant possibility for decarbonization. However, ...
Background: The “gut–skin axis” has been proposed to play an important role in the development and symptoms of atopic dermatitis. Therefore, we have constructed an interpretable machine learning ...
Introduction: Understanding human actions in complex environments is crucial for advancing applications in areas such as surveillance, robotics, and autonomous systems. Identifying actions from ...
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