IEEE

An XGBoost-SHAP Model for Energy Demand Prediction With Boruta–Lasso Feature Selection

Abstract: Energy demand prediction is essential in ensuring national energy security, promoting high-quality economic development, advancing sustainable development, optimizing the energy structure, ...
The Lancet

Machine learning prediction of 1-year mortality in older patients with heart failure: a nationwide, multicenter, prospective cohort study

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
Psychology Today

AI-Decoded Brain Signals May Help Paralyzed Regain Movement

New AI model decodes brain signals captured noninvasively via EEG opens the possibility of developing future neuroprosthetics ...
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Carson-Newman University

Active Learning vs. Passive Learning: Why It Matters For Online Students

If you’ve ever finished an online lecture and realized you barely remember what was covered, you’ve experienced the difference between active vs. passive learning. In virtual classrooms, it’s easy to ...
EurekAlert!

Machine learning-guided gradient dual-proton conducting catalytic layers for high temperature proton exchange membrane fuel cells in aviation

High-temperature proton exchange membrane fuel cells (HT-PEMFCs) are highly promising for next-generation aviation, as they can operate above 160 °C and tolerate impurities in the fuel. However, they ...
Beebom

What is the Difference Between Deep Learning and Machine Learning

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...
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 ...
Houston Chronicle

Parents fear for future of St. Thomas program that benefits students with learning differences

Houston-area parents are worried about the future of a groundbreaking program for students with learning differences and neurological conditions as the University of St. Thomas shuffles the program to ...
TCTMD

TCT 896: Sex differences in atherosclerotic coronary artery disease patterns assessed by Pullback Pressure Gradient

TCT 895: The Diagnostic Utility of Left Ventricular Ejection Fraction to Global Longitudinal Strain Ratio (LVEF/GLS) in Predicting Severity of Stable Coronary Artery Disease: A Cross-Sectional Study ...
Frontiers

Predicting food prices in Kenya using machine learning: a hybrid model approach with XGBoost and gradient boosting

Introduction: Food price volatility continues to be a significant concern in Kenya's economic development, posing challenges to the country's economic stability. Methodology: This study examines the ...
Frontiers

PiCCO hemodynamic parameters in cardiogenic shock: prediction of LVEF, NT-proBNP and MACE based on XGBoost machine learning model

Department of Cardiology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China Introduction: This study used the Extreme Gradient Boosting (XGBoost) machine learning model to ...