Frontiers

XGBoost-based machine learning model combining clinical and ultrasound data for personalized prediction of thyroid nodule malignancy

Purpose: Thyroid ultrasound is a primary tool for screening thyroid nodules (TNs), but existing risk stratification systems have limitations. Nowadays, machine learning (ML) offers advanced ...
IEEE

Interpretable Prediction of a Decentralized Smart Grid Based on Machine Learning and Explainable Artificial Intelligence

Abstract: The concept of a decentralized smart grid has emerged as a viable approach for efficiently managing and distributing electrical energy. Ensuring the stability and reliability of the grid, ...
IEEE

Deep Learning Approaches for EEG-Motor Imagery-Based BCIs: Current Models, Generalization Challenges, and Emerging Trends

Abstract: This study critically examines the evolution of deep learning (DL) for electroencephalogram (EEG) based motor imagery (MI) decoding with a focus on real-time Brain Computer Interfaces (BCIs) ...
Frontiers

Development and validation of a machine learning-driven mitochondrial gene signature for the diagnosis of breast cancer

Background: Breast cancer (BC) ranks among the most prevalent malignant tumors in women globally, with mitochondrial dysfunction constituting one of its pathogenic mechanisms. Objectives: To ...