Machine learning-driven reconstruction of the climatological geomagnetic diurnal variations at middle to low latitudes

# Artificial Intelligence-Enabled Quantification of Cube and Goss Textures in Polycrystalline Materials: A Comprehensive Review of Machine Learning, Deep Learning, and EBSD-Based Characterization Approaches

Sudhakar Geruganti

## ALTERNATIVE TITLES ### Alternative Title 1 (Comprehensive)**"AI-Driven Analysis of Cube {100}<001> and Goss {110}<001> Textures: Machine Learning, Deep Learning, and Generative Models for Crystallographic Texture Quantification in Metallurgical Engineering"** ### Alternative T…Read more

A Systematic Review of Machine Learning, Deep Learning, and Explainable AI Approaches for Cardiac Disease Prediction

Sunanda Budihal, Sheetalrani Kawale, Abhishek Angadi

The cardiovascular (Cardiac) disease (CVD) is another factor that causes death among the global population most, and this is the reason why there is a high necessity to implement proper, effective, and interpretive diagnostic systems. The usage of machine learning (ML), deep lear…Read more

Also available via: European Organization for Nuclear Research

RAQA-AutoML: An Integrated Solution for Automated Machine Learning

Abdullah Kaviani Rad

Overview AutoML-Lite is a powerful, user-friendly desktop application designed to democratize machine learning by automating the entire modeling pipeline. Built with Python and PyQt6, it provides a comprehensive GUI-based environment for data preprocessing, feature engineering, m…Read more

Client Recognition Using Text-Dependent Voice Biometrics: A Machine Learning and Deep Learning Approach

Annual Methodological Archive Research Review

Enhancing Cardiovascular Disease Diagnosis through Data-Driven Feature Analysis and Cross-Validated Machine Learning Models

Abhilash Butola

Abstract - Cardiovascular diseases are a major global health problem, accounting for 17.9 million deaths per year and constituting 32 percent globally. According to the World Health Organization, the disease in people is due to an unhealthy diet,such as the intake of more junk fo…Read more

Event-Based Prediction of Liquidity Sweep Dynamics in XAUUSD Using Machine Learning

Vanshvardhan Sharma

This paper develops a machine learning framework for detecting and predicting liquidity sweep events in XAUUSD using event-based market microstructure analysis. Using 15-minute data from 2014–2024, the study formalizes liquidity sweeps as a binary classification problem evaluated…Read more