Researchers have developed a new "emotionally aware" AI-based model for classifying mental health conditions, which could ...
David Gerbing from the School of Business at Portland State University introduces lessR, a tool designed to facilitate professional-quality data visualizations and data analysis without programming re ...
Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...
Mathematics In AI: Mathematical concepts such as statistics and probability form the foundation of Artificial Intelligence (AI) and its branches like Machine Learning and Deep Learning. Machine ...
Objective To investigate the association between attention-deficit/hyperactivity disorder (ADHD) and cardiometabolic risk profile at the time of type 2 diabetes (T2D) diagnosis and examine ...
Abstract: In this paper, a novel nonlinear technique for hyperspectral image (HSI) classification is proposed. Our approach relies on sparsely representing a test sample in terms of all of the ...
Abstract: In the past decades, the ensemble systems have been shown as an efficient method to increase the accuracy and stability of classification algorithms. However, how to get a valid combination ...
Objectives To assess the outcomes of patients undergoing open abdominal surgery at a National Referral Hospital in Tanzania. Design A prospective, observational, single-arm cohort study. Setting Dar ...
Researchers developed a washable textile-based IDC strain sensor that tracked yoga-inspired movements with 94.4% record-level ...
1 Clinical Epidemiology Research and Training Unit, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USA 2 Data Coordinating Center, Boston University School of ...
Bigger has defined AI from day one. New data says task-specific small models beat frontier LLMs on accuracy, cost and speed — ...
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