Randomized Explainable Machine Learning Models for Efficient Medical Diagnosis

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Urology, Nephrology, Medical Imaging, Oncology, Cardiovascular System,
medical diagnosis   randomized models   explainable artificial intelligence   extreme learning machines   random vector functional link   big data   deep learning  

New Breakthrough in Intelligent Medical Diagnosis: Randomized Explainable Machine Learning Models Drive Efficient Medical Diagnostics I. Academic Background and Research Motivation In recent years, Deep Learning (DL) models have played a crucial role in the field of healthcare. By processing vast amounts of medical data, DL significantly improves t...

Probing Nanoscale Structural Perturbation in a WS2 Monolayer via Explainable Artificial Intelligence

Chemistry, Nanoscience, Materials Science, Information Science, Semiconductors and Information Devices, Artificial Intelligence,
nanoscale   structural perturbation   explainable artificial intelligence   Raman spectroscopy   machine learning  

Background Introduction Two-dimensional (2D) materials exhibit significant potential in fields such as nanoelectronics and optoelectronics due to their unique physical and chemical properties. However, structural perturbations at the nanoscale have a profound impact on their performance. Traditional characterization methods like Raman spectroscopy,...

An Improved and Explainable Electricity Price Forecasting Model via SHAP-Based Error Compensation Approach

Engineering, Energy Engineering, Information Science, Electronic Information, Artificial Intelligence,
electricity price forecasting   explainable artificial intelligence   SHAP method   error compensation   neural networks   electricity markets   price volatility  

Improved Electricity Price Forecasting Model Based on SHAP and Its Explainability Analysis Background and Research Motivation Electricity price forecasting (EPF) models have become a hot research topic in recent years, particularly due to the financial impact of market volatility on stakeholders. Especially in European energy markets, recent years ...

Empowering Glioma Prognosis with Transparent Machine Learning and Interpretative Insights Using Explainable AI

Information Science, Computer Science, Artificial Intelligence, Medicine, Basic Medical Sciences, Neurology, Oncology,
glioma   molecular makeup   explainable artificial intelligence   SHAP   LIME   Qlattice   ELI5   machine learning  

Enabling Explainable Artificial Intelligence for Glioma Prognosis: Translational Insights from Transparent Machine Learning Academic Background This study is dedicated to developing a reliable technique to detect whether patients have a specific type of brain tumor—glioma—using various machine learning methods and deep learning methods, combined wi...