Low-cost AI could transform health care logistics in low- and middle-income countries

Managing a medical supply chain in low- and middle-income countries can mean navigating a landscape prone to extreme and ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
Scientific Research Publishing

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features ()

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...
IEEE

Predictive Analysis of Network-Based Attacks by Hybrid Machine Learning Algorithms Utilizing Bayesian Optimization, Logistic Regression, and Random Forest Algorithm

Abstract: These days, intrusion detection systems are one of the newest trends in society. These technologies serve as a defense against a variety of security breaches, the number of which has been ...
LinkedIn

Logistic Regression in Machine Learning

The core idea behind Logistic Regression is to estimate the probability that an instance belongs to a particular class. This transformation allows the model to express confidence in a particular class ...
Law

Training Alone Is Not Enough: Lessons From 'Recentive' and USPTO AI Examples on Patent Eligible Machine-Learning Claims

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...
Nature

Comparison between logistic regression and machine learning algorithms on prediction of noise-induced hearing loss and investigation of SNP loci

To compare the comprehensive performance of conventional logistic regression (LR) and seven machine learning (ML) algorithms in Noise-Induced Hearing Loss (NIHL) prediction, and to investigate the ...
Nature

Comparative study of XGBoost and logistic regression for predicting sarcopenia in postsurgical gastric cancer patients

The use of machine learning (ML) techniques, particularly XGBoost and logistic regression, to predict sarcopenia among postsurgical gastric cancer patients has gained significant attention in recent ...
GitHub

Lung Cancer Prediction Project

In this project, we leverage the power of artificial intelligence in healthcare to predict lung cancer risks. By employing various machine learning techniques, we aim to assist medical professionals ...
Scientific Research Publishing

Machine Learning-Based Classification of Coronary Heart Disease: A Comparative Analysis of Logistic Regression, Random Forest, and Support Vector Machine Models ()

1 Department of Business Information System, Central Michigan University, Mount Pleasant, MI, USA. 2 Department of MPH, Central Michigan University, Mount Pleasant, MI, USA. 3 Department of ...
eWeek

What is Logistic Regression? A Comprehensive Guide

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...