A nomogram based on the SVM machine learning model was constructed to predict the risk of COVID-19 severity. The model showed high accuracy and…
Browsing: SVM
This article explores the potential of machine learning and explainable artificial intelligence algorithms to automate the process of clinical gait analysis for foot disorders.…
This article explores key AI algorithms for healthcare applications, including machine learning, linear regression, decision trees, random forests, and SVM. These algorithms are reshaping…
This article explores some of the most popular machine learning algorithms used for data classification. These include Decision Trees, Random Forest, Support Vector Machines…
This paper reviews existing research on brain tumor detection and discusses the importance of medical imaging modalities, particularly MRI. It proposes a method involving…
Machine learning is a subset of artificial intelligence that enables systems to learn and improve from experience autonomously. This article provides an overview of…
This article discusses the use of XAI techniques for predicting concrete strength. It outlines the five fundamental stages of the machine learning framework for…
Data science is a constantly evolving field that requires mastery of essential algorithms to uncover insights from datasets. This article outlines 10 important algorithms,…
This article discusses recent research on the use of machine learning and deep learning models for burn diagnosis. Otsu’s technique is used to remove…
This study examined the use of radiomic features extracted from initial CT images before TKI-PD-1 treatment to predict the response of hepatocellular carcinoma (HCC)…