AZoBuild

New Study Combines Metakaolin and AI for Smarter Concrete Design

The integration of AI in concrete design using metakaolin leads to stronger, eco-friendly materials, advancing sustainability ...
Scientific Research Publishing

H-UQ-MFF: Hybrid Uncertainty-Aware Multi-Feature Fusion for Clinically-Translatable Glaucoma Detection with FDA-Compliant Validation ()

Although artificial intelligence (AI) has demonstrated potential in automating glaucoma screening, there is still a ...
IEEE

Classifying Fake News with a Large-Scale Dataset Using Machine Learning Approaches

Abstract: In an era where the vast influx of content increasingly compromises the authenticity of information, identifying false information has emerged as a pressing concern. This research addresses ...
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 ...
IEEE

Advanced SVM-Enhanced Machine Learning Algorithm for Optimizing Invasive Detection in Smart Grids

Abstract: Given the fact that smart grids integrate distributed energy resources and advance communication technologies, which have high security vulnerability to the attack of denying service (DoS), ...
Frontiers

Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm

Osteoporosis is a metabolic bone disease characterized by a decrease in the amount of bone per unit volume. It is highly prevalent and has a harsh impact on patients' lives. The development of ...
Frontiers

Postpartum depression risk prediction using explainable machine learning algorithms

Postpartum depression (PPD) is a common and serious mental health complication after childbirth, with potential negative consequences for both the mother and her infant. This study aimed to develop an ...
VentureBeat

How to detect poisoned data in machine learning datasets

Almost anyone can poison a machine learning (ML) dataset to alter its behavior and output substantially and permanently. With careful, proactive detection efforts, organizations could retain weeks, ...