Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

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 ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

To his credit, Kasy is a realist here. He doesn’t presume that any of these proposals will be easy to implement. Or that it will happen overnight, or even in the near future. The troubling question at ...

Enterprise adoption of cognitive intelligence platforms has accelerated, yet executive confidence has not kept pace. Many deployments promise ...

In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate safely and efficiently using a Transformer model.

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

Abstract: High-quality predictions of key indicators are essential to maintain stable production in the iron and steel industry. However, most existing prediction methods rely on manually designed ...

Abstract: This study examines how self-supervised learning may improve 3D medical imaging performance and readability by enhancing feature models and grouping. The recommended strategy combines ...