By transforming everyday smartphone signals into high-resolution mobility data, researchers have reconstructed how residents ...

Researchers have developed an advanced artificial intelligence (AI) framework designed to significantly improve the forecasting of carbon dioxide emissions in the aviation sector. ACGRIME is an ...

Oracle-based quantum algorithms cannot use deep loops because quantum states exist only as mathematical amplitudes in Hilbert ...

Technology is revolutionising how we gather and assess data on nature, presenting huge benefits and no little irony ...

More than half of transplant recipients in a large analysis developed chronic graft-versus-host disease, and 15% died from ...

A research team from The Hong Kong University of Science and Technology (HKUST) has developed GrainBot, an AI-enabled toolkit ...

A research team from The Hong Kong University of Science and Technology (HKUST) has developed GrainBot, an AI-enabled toolkit that automatically ...

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

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

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

A publicly available AI tool correctly predicted approximately twice as many children with acute lymphoblastic leukemia who would relapse as three expert clinicians.XGBoost, a boosting algorithm, had ...

Abstract: This study uses an AI-enhanced cybersecurity events dataset to utilize the effectiveness of leveraging machine learning algorithms Logistic Regression, Decision Tree, and Random Forest for ...