Cardiovascular disease (CVD) remains the foremost contributor to global illness and death, underscoring the critical need for effective tools that can predict risk at early stages to support ...

The field of neuroimaging has undergone profound transformation in recent years, driven primarily by rapid advances in machine learning (ML), and especially deep learning (DL), techniques. These ...

New Delhi: A team of Indian and US researchers has developed an artificial intelligence (AI)-based technique to detect diabetes without the traditional blood tests. The technique can detect whether a ...

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...

Abstract: The IoT has emerged as a significant target for cyber-attacks, particularly with a focus on the routing protocol for low-power and lossy networks (RPL) within Wireless Sensor Networks (WSNs) ...

ABSTRACT: The recent surge in demand for timely and accurate health information has highlighted the need for more advanced data analysis tools. To reduce the incidence of preventable medical errors, ...