A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...
1 Information Statistics Center, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 2 School of Computer Science and Technology, Hubei Business ...
Exploring the Perspectives of Pediatric Health Care Providers, Youth Patients, and Caregivers on Machine Learning Suicide Risk Classification: Mixed Methods Study ...
Abstract: The increasing penetration of inverter-based distributed generation (DG) into power grids improves access to electricity and provides a significant possibility for decarbonization. However, ...
This Research Topic explores the application of Machine Learning (ML) and Deep Learning (DL) methods in Neuromarketing and Consumer Neuroscience. Rather than following the prevailing “AI trend” ...
ABSTRACT: Pregnancy presents a unique clinical scenario where the safety of pharmacological interventions is of paramount importance. The potential teratogenic risks associated with drug intake during ...
In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from ...
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