MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...
Machine learning is revolutionizing fundamental science by tackling long-standing mathematical challenges. A key example is ...
Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...
Abstract: This study explores the collision of suspension droplets against solid dry surfaces (substrates). It applies and compares multiple machine learning (ML) models for the classification of ...
AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
This is read by an automated voice. Please report any issues or inconsistencies here. If you came out of “The Smashing Machine” thinking “that must have hurt,” it was by design. Director Benny Safdie ...
Introduction: This study aimed to develop a diabetic retinopathy (DR) Prediction model using various machine learning algorithms incorporating the novel predictor Triglyceride-glucose index (TyG).
1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
Changes in NEN classification in 2013 may partly explain the rise in EOCRC incidence, with NEN rates surging before 2013 and declining thereafter. EOCRC incidence increased among individuals aged 15 ...
Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
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