Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

Microsoft deletes blog telling users to train AI on pirated Harry Potter books

The blog recommended that users learn to train their own AI models by downloading the Harry Potter dataset and then uploading text files to Azure Blob Storage. It included example models based on a ...
Tech Xplore

'Learn-to-Steer' method improves AI's ability to understand spatial instructions

Researchers from the Department of Computer Science at Bar-Ilan University and from NVIDIA's AI research center in Israel ...
Cyber Defense Magazine

Deepfakes, Synthetic Media, and Digital Trust: The Cybersecurity Implications of Deepfake Technology and Methods for Detection and Mitigation

Introduction The proliferation of deepfake technology, synthetic media generated using advanced artificial intelligence techniques, has emerged as a ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

Inside the Race to Achieve the Singularity—Before Moore’s Law Runs Out

AI optimists envision a future where artificial general intelligence (AGI) surpasses human intelligence, but the path remains riddled with scientific and logistical hurdles.
Scientific Research Publishing

Accuracy and Response Speed of Eye Center Annotation Using Eye Movement Models: Validating the Effectiveness of Eyesight Detection ()

Optokinetic Nystagmus (OKN) is a natural reflexive eye movement in oculomotor studies, reflecting the health status of the visual system. Through accurate eye center annotation, physicians can observe ...

LearningMole Launches AI Literacy Initiative to Help Teachers and Parents Prepare Children for an AI-Enabled World

Educational platform announces expanded course programme addressing critical thinking, responsible use, and AI ...
IEEE

Benchmarking Machine Learning Algorithms for Bearing Fault Classification Using Vibration Data: A Deployment-Oriented Study

Abstract: This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in ...
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 ...
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 ...