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Noise-powered chips use heat for computing and can crush classic power limits

Researchers have built a small-scale computer that runs on thermal noise, the random electrical fluctuations that conventional chip designers spend billions trying to suppress. The device, called a ...

Machine learning can predict preeclampsia by week 34 of pregnancy

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...

Letting atomic simulations learn from phase diagrams

A new computational method allows modern atomic models to learn from experimental thermodynamic data, according to a ...
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 ...
Frontiers

Machine learning-based improved method for estimating long-term failure probability with high efficiency of bank slope

Affected by water level and rainfall, the failure probability of bank slope is of great time-dependent characteristics. Combining the random field theory with Monte Carlo simulation strategy to ...
Frontiers

Prediction of hemorrhagic transformation after thrombolysis based on machine learning models combined with platelet distribution width-to-count ratio

Hemorrhagic transformation (HT) is a common and potentially serious complication following intravenous thrombolysis (IVT) in patients with acute ischemic stroke (AIS). Despite its high incidence, ...
C&EN

Evaluating Machine Learning Models for Molecular Property Prediction: Performance and Robustness on Out-of-Distribution Data

Department of Pharmaceutical Sciences, Division of Pharmaceutical Chemistry, Faculty of Life Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria Christian Doppler Laboratory ...
IEEE

Integrating Machine Learning Models With Probability Distribution Methods for Extreme Flood Risk Assessment

Abstract: Climate change exacerbates flooding risks, a frequent and devastating natural calamity, particularly in flood-prone regions such as Pakistan. Constraints on computation and inadequate data ...
IEEE

A Survey of Machine Learning Techniques for Optimal Capacitor Placement and Sizing in Smart Distribution Networks

Abstract: The increasing complexity of modern power distribution networks necessitates advanced strategies for reactive power compensation, particularly in capacitor placement and sizing. Traditional ...