Advancing Neurological Disease Prediction through Machine Learning Techniques

A study explores how AI and ML can improve early detection of neurological diseases, including Parkinson’s disease, ...
Visual Studio Magazine

Implementing k-NN Classification Using C#

Dr. James McCaffrey of Microsoft Research presents a full demo of k-nearest neighbors classification on mixed numeric and categorical data. Compared to other classification techniques, k-NN is easy to ...
leewayhertz

AI in anomaly detection: Use cases, methods, algorithms and solution

In this era of digital transformation, buzzwords like ‘Industry 4.0’ and ‘digitalization’ have become part of our daily vocabulary. But behind these trendy terms lies a potent technological innovation ...
Frontiers

Causative Classification of Ischemic Stroke by the Machine Learning Algorithm Random Forests

Prognosis, recurrence rate, and secondary prevention strategies differ by different etiologies in acute ischemic stroke. However, identifying its cause is challenging. We retrospectively reviewed the ...
Scientific Research Publishing

Basic Tenets of Classification Algorithms K-Nearest-Neighbor, Support Vector Machine, Random Forest and Neural Network: A Review ()

1 Department of Basic Sciences, School of Basic and Biomedical Sciences, University of Health and Allied Sciences, Ho, Ghana. 2 Department of Statistics and Actuarial Science, University of Ghana, ...
IEEE

Medical Health Big Data Classification Based on KNN Classification Algorithm

Abstract: The rapid development of information technology has led to the development of medical informatization in the direction of intelligence. Medical health big data provides a basic data resource ...
IEEE

Sparse Coefficient-Based ${k}$ -Nearest Neighbor Classification

Abstract: K-nearest neighbor rule (KNN) and sparse representation (SR) are widely used algorithms in pattern classification. In this paper, we propose two new nearest neighbor classification methods, ...