Light in the forest: Computer simulations show increased tree diversity from competition for canopy light

If a tree falls in the forest, it can create an opening for more incoming light, and that makes a significant impact on the surrounding environment, according to new research. An international science ...
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 ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
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

Future Directions in Electric Load Forecasting: Leveraging Random Forest for Improved Accuracy

Abstract: With the advancement of power technologies in the modern era, electric load forecasting has become increasingly crucial in domains including power grid layout optimization, electricity ...
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 ...