The field of intelligent energy systems has witnessed a remarkable transformation owing to innovations in machine learning. Over the past few decades, the ...
Abstract: Sparse and unevenly distributed soil samples across the northern high-latitude region greatly limit the accuracy of soil organic carbon (SOC) mapping. Substantial discrepancies, therefore, ...
Background Hypertrophic cardiomyopathy (HCM) is associated with an increased risk of sudden cardiac death (SCD), and myocardial fibrosis plays a central role in the pathophysiology process.
New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of floods. The studies, published in Water Resources Research and the Proceedings ...
You're probably a little tired of reading or hearing about AI, right? Well, if that's the case, then you're in the right place because here, we're going to talk about machine learning (ML). Yes, it's ...
ABSTRACT: This paper proposes a hybrid machine learning framework for early diabetes prediction tailored to Sierra Leone, where locally representative datasets are scarce. The framework integrates ...
This study evaluates the effect of common resampling strategies on imbalanced binary classification by benchmarking multiple classifiers—including linear models, distance-based methods, tree learners, ...
Traditional QSRR models are limited to single-column predictions, hindering adaptability across diverse LC setups in pharmaceutical settings. The new ML-based approach predicts retention times using ...
(L) First and co-corresponding author Charlie Wright, PhD, St. and (R) co-corresponding author Paul Geeleher, PhD, both of the St. Jude Department of Computational Biology. (MEMPHIS, Tenn. – December ...
Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...
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