Abstract: This study is a comparison of six supervised learning algorithms, including Logistic Regression, Support Vector Machines (SVM), Decision Trees, Random Forests, k-Nearest Neighbors (kNN), and ...
The Bureau of Reclamation (Reclamation) projects 2 – 5-year Colorado River Basin (CRB) system conditions for stakeholders using their Colorado River Mid – Term Modeling System (CRMMS). As inputs, this ...
The objective of this project is to build and compare multiple machine learning classification models to predict wine quality. The task involves classifying wines into two categories: Good Quality ...
Exploring the Past and Current Landscape of Biomarker-Driven Clinical Trials Through Large Language Models First, we pretrained the encoder of a transformer-based network using a self-supervised ...
Antimicrobial resistance (AMR) represents an escalating global health threat, demanding diagnostic strategies capable of rapid, accurate, and comprehensive pathogen characterization. Genomic ...
ABSTRACT: Foot-and-Mouth Disease (FMD) remains a critical threat to global livestock industries, causing severe economic losses and trade restrictions. This paper proposes a novel application of ...
Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for millions of deaths each year according to the World Health Organization (WHO). Early detection of these diseases ...
Abstract: Network traffic classification (NTC) is vital for efficient network management, security, and performance optimization, particularly with 5G/6G technologies. Traditional methods, such as ...
We developed a classifier to infer acute ischemic stroke severity from Medicare claims using the modified Rankin Scale at discharge. The classifier can be used to improve stroke outcomes research and ...
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