The BMJ

When I use a word . . . Artificial intelligence—predicting and detecting adverse drug reactions

The Law of Mass action predicts that all adverse drug reactions are related to the concentration of the drug at the site of ...
Journal of Medical Internet Research

Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review

Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...
GitHub

3rd Workshop on Causal Inference and Machine Learning in Practice

The 3rd Workshop on Causal Inference and Machine Learning in Practice at KDD 2025 aims to bring together researchers, industry professionals, and practitioners to explore the application of causal ...
Ecommerce Fastlane

What Are AI Algorithms? Types of AI Algorithms + Use Cases

The line between human and artificial intelligence is growing ever more blurry. Since 2021, AI has deciphered ancient texts ...
IEEE

Reducing Unnecessary Handovers Using Logistic Regression in 5G Networks

Abstract: The evolution of wireless communication has brought great benefits to society, such as multi-connectivity, increased connection speed, low latency, and elevated throughput. However, it has ...
Frontiers

A prediction method for older adult care service demand combining improved RF algorithm and logistic regression

Academy of Art and Design, Yancheng Teachers University, Yancheng, China Introduction: With the acceleration of global aging, the accurate prediction of care service demand for older adults is of ...
IEEE

A Comprehensive Machine Learning Approach for Wild Fire Detection and Classification Using Squeezenet and Ridge Regularized Logistic Regression

Abstract: Wild fire is a serious environmental and socioeconomic menace and therefore any effort aimed at the early and accurate detection of wild fire has to be very useful. This paper proposes a ...