That challenge is examined in the study Towards Eco-Friendly Cybersecurity: Machine Learning-Based Anomaly Detection with ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

A research paper by scientists from Beihang University proposed a machine learning (ML)-driven cerebral blood flow (CBF) prediction model, featuring multimodal imaging data integration and an ...

1 Department of Nephrology, Nanchong Central Hospital Affiliated to North Sichuan Medical College, Nanchong, China 2 Department of Nephrology, Guangyuan Central Hospital, Guangyuan, China Background: ...

An automated MATLAB application for brain tumor detection and segmentation from MRI images. This project uses image processing and a Support Vector Machine (SVM) classifier to identify and highlight ...

Abstract: Cancer is a heterogeneous disease that can spread to any body part. Breast cancer is one of the most dangerous cancers among women, contributing significantly to mortality worldwide. This ...

William Parks is a Game Rant editor from the USA. Upon graduating from the University of Southern California’s School of Cinematic Arts, William entered the realm of fine arts administration, ...

1 Faculty of Mathematics and Computer Science,, Felix Houphouët-Boigny University, Abidjan, Côte d’Ivoire. 2 Institute for Mathematical Research (IRMA), Abidjan, Côte d’Ivoire. 3 Higher Teacher ...

Background: To establish a classification model for assisting the diagnosis of type 2 diabetes mellitus (T2DM) complicated with coronary heart disease (CHD). Methods: Patients with T2DM who underwent ...

Abstract: Animals can be identified by using various machine learning techniques among which a hybrid model combines multiple techniques together. In this approach a hybrid model with Convolutional ...