Beebom

AI vs Machine Learning: What is the Difference?

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...
Scientific Research Publishing

Comparative Study of Machine Learning Techniques for Early Detection of Heart Diseases ()

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for millions of deaths each year according to the World Health Organization (WHO). Early detection of these diseases ...
Morningstar

Machine Learning Can Forecast Which Stock Factors Will Outperform

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...
The American Journal of Managed Care

Novel Machine Learning Model Improves MASLD Detection in Type 2 Diabetes

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...
ahajournals.org

Abstract Fri013: AI-Driven Gait Classification for Peripheral Artery Disease (PAD) Detection Using Machine Learning and Nonlinear Gait Dynamics

Introduction: Peripheral Artery Disease (PAD) is a progressive vascular disorder impairing mobility, raising fall risk, and reducing quality of life. Early detection is key to preventing amputations ...
IEEE

Anomaly Detection in IoT Networks: A Deep Learning Approach Using Autoencoders

Abstract: The current fast proliferation of the Internet of Things (IoT) networks has made anomaly detection and security more difficult. Traditional methods are not able to detect hostile activities ...
IEEE

Machine learning-based intrusion detection and prevention using cross-layer features in Internet of Things (IoT) networks

Abstract: The IoT has emerged as a significant target for cyber-attacks, particularly with a focus on the routing protocol for low-power and lossy networks (RPL) within Wireless Sensor Networks (WSNs) ...
Frontiers

Evaluating machine learning models for stroke prediction based on clinical variables

Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as the Framingham ...
news.ucsc

WiFi signals can measure heart rate—no wearables needed

Computer Science and Engineering Ph.D. student Nayan Bhatia demonstrates Pulse-Fi, technology that uses WiFi signals to measure a person's heart rate. Heart rate is one of the most basic and important ...
Frontiers

An intelligent identification for pest and disease detection in wheat leaf based on environmental data using multimodal data fusion

1 School of Mathematics and Statistics, Fuyang Normal University, Fuyang, China 2 State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou, Hainan, China The ...