IEEE

A Self-Adaptive Data Preprocessing Pipeline for Machine Learning: An Automated and Dynamic Approach

Abstract: The optimization and generalization of performance of a machine learning model is profoundly influenced by efficient data preprocessing. A machine's learning model does not perform to its ...
C&EN

Historical Data Mining Deep Dive into Machine Learning-Aided 2D Materials Research in Electrochemical Applications

You are free to share (copy and redistribute) this article in any medium or format and to adapt (remix, transform, and build upon) the material for any purpose, even commercially within the parameters ...
Scientific Research Publishing

AI-Driven Prediction of Drug Safety in Pregnancy: A Machine Learning Approach ()

1 Department of Neuroscience, Institute of Psychopathology, Rome, Italy. 2 Department of Computer Engineering (AI), University of Genova, Genova, Italy. Evaluating drug safety during pregnancy remains ...
Frontiers

Non-invasive detection of Parkinson’s disease based on speech analysis and interpretable machine learning

Objective: Parkinson’s disease (PD) is a progressive neurodegenerative disorder that significantly impacts motor function and speech patterns. Early detection of PD through non-invasive methods, such ...
Frontiers

Predicting overall survival in glioblastoma patients using machine learning: an analysis of treatment efficacy and patient prognosis

Introduction: Glioblastoma (GBM), the most aggressive primary brain tumor, poses a significant challenge in predicting patient survival due to its heterogeneity and resistance to treatment. Accurate ...
GitHub

Lung Cancer Prediction Project

In this project, we leverage the power of artificial intelligence in healthcare to predict lung cancer risks. By employing various machine learning techniques, we aim to assist medical professionals ...