A large study applies advanced machine learning to identify shared risk factors and predictors of disease onset in patients with epilepsy and depression.
Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP ...
Patent covers machine learning techniques for ECG denoising, rhythm classification, sample-level labelling, wearable cardiac ...
aDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for ...
BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
Abstract: Automatic arrhythmia detection requires effective and clear models because cardiovascular disease is increasingly common. Convolutional neural networks (CNNs) have proven to be the most ...
Abstract: Predictive maintenance, utilising anomalous sound classification, demonstrates a strong potential to identify mechanical faults in industrial machinery. This research proposes a machine ...