A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.

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

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Background: The purpose of this study is to use a variety of machine learning (ML) algorithms to build a risk prediction model for nursing students’ social anxiety, select the optimal model, and ...

Objectives Current prediction models for disease progression to AIDS in people living with HIV primarily rely on traditional statistical methods. This study aimed to develop and compare four machine ...

Abstract: Phishing website is a form of mimicking legitimate sites with the purpose of stealing user’s confidential data. It is a growing threat in the digital age due to its potential to cause ...

Objective: This study attempts to identify risk factors associated with postoperative pain in patients with lumbar spinal stenosis undergoing transforaminal lumbar interbody fusion (TLIF) and to ...

This repository contains the complete implementation of a BSc Statistics dissertation investigating supervised learning approaches for fraud risk scoring in Nigerian financial transactions. The ...

1 Department of Neuroscience, Institute of Psychopathology, Rome, Italy. 2 Department of Computer Engineering (AI), University of Genova, Genova, Italy. Elderly individuals undergoing long-term ...