While multiple machine learning (ML) algorithms offered similar predictive performance, the cost-effective analysis revealed ...

Researchers from Carnegie Mellon University’s School of Computer Science developed a new approach to bridge this gap between available data and actionable insight, creating personalized models to help ...

The prediction of long-term outcomes in ischemic stroke patients may be useful in treatment decisions. Machine learning techniques are being increasingly adapted for use in the medical field because ...

AI’s growth is limited by poor-quality data, not model size. Human expertise in data curation, decentralized feedback and ...

Current care in multiple sclerosis (MS) primarily relies on infrequently obtained data such as magnetic resonance imaging, clinical laboratory tests or clinical history, resulting in subtle changes ...

The purpose of this article is to provide a comprehensive review for the use of supervised and unsupervised Machine Learning as well as Deep Neural Networks for charging behavior analysis and ...