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 ...
Risk-based strategies are superior to the U.S. Preventive Services Task Force (USPSTF) criteria for optimizing efficiency and ...
Five years after Covid, apparel logistics has evolved through regional fulfillment, stronger 3PLs, smarter last-mile delivery ...
Large language models (LLMs) are rapidly being integrated into clinical workflows, supporting tasks such as diagnosis ...
Background Sociodemographic inequalities impact patients with non-small cell lung cancer (NSCLC). Advances in novel ...
Researchers developed a washable textile-based IDC strain sensor that tracked yoga-inspired movements with 94.4% record-level ...
Objectives To examine primary care contacts among individuals with eating disorders (EDs) and assess differences across ...
[2] Structured Matrix Scaling for Multi-Class Calibration (see also: experiments) [3] A Variational Estimator for Lp Calibration Errors (see also all experiments) [4] CalArena: A Large-Scale Post-Hoc ...
The BERT model achieved the highest impact factor tertile classification accuracy of 75.0%, followed by an accuracy of 71.6% for XGBoost and 65.4% for logistic regression. Similarly, BERT achieved 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 ...
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 ...
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