The Women Who Travel Power List 2026

From record-setting adventurers to diasporic filmmakers and chefs, these are the women defining the way we see—and ...
RMD Open

Distinct pattern of comorbidities hinders treatment target attainment in SLE through persistent disease activity and delayed glucocorticoid tapering: longitudinal data fro…

Background Remission and low-disease activity are recommended targets in systemic lupus erythematosus (SLE), yet many ...
Scientific Research Publishing

Cybersecurity and Forensic Audio Analysis: Deepfake Detection Based on Mfcc, Audio-Text Disconsistency, and Prosodic Features ()

1 Department of Computer and Instructional Technologies Education, Gazi Faculty of Education, Gazi University, Ankara, Türkiye. 2 Department of Forensic Informatics, Institute of Informatics, Gazi ...
Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
GitHub

Shubhang-Kuber/DTL-Project

A comprehensive machine learning platform that predicts student dropout risk using dual algorithms (Random Forest & XGBoost with SMOTE) and provides personalized, data-driven support recommendations ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
IEEE

AI-Driven Classification of Tsunami-Generating Earthquakes: Harnessing Random Forest, SVM, and Logistic Regression for Early Detection

Abstract: Predicting whether an earthquake will generate a tsunami is critical for early warning systems and disaster mitigation. In this study, we present an AI-driven approach to classify ...
IEEE

Random Forest Algorithm Based Colour Classification of First Roasted Tobacco

Abstract: This study proposes an intelligent classification method of tobacco colour based on random forest algorithm. By collecting six grades of tobacco samples from 87 varieties of Yunnan Yuxi ...