BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

The poster highlights an NSF award shared by Nelson and Casey Kennington, Boise State University Foundation Board Endowed Professor of Computer Science, and showcases their progress in expanding ...

Quiq reports on the role of automation in customer service, highlighting tools like AI for questions, ticket classification, ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Abstract: Recent research has revealed that using machine learning systems for the analysis of genetic data could reliably detect Alzheimer’s disease. The interpretability of these models, however, ...

Abstract: Data stream learning is an emerging machine learning paradigm designed for environments where data arrive continuously and must be processed in real time. Unlike traditional batch learning, ...

Early identification and prediction of persistent SA-AKI are crucial. Objective: The aim of this study was to develop and validate an interpretable machine learning (ML) model that predicts persistent ...

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 ...

State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, P. R. China Sino-Danish College, ...