IEEE transactions on biomedical circuits and systems
32191898
The primary objective of this paper is to build classification models and strategies to identify breathing sound anomalies (wheeze, crackle) for automated diagnosis of respiratory and pulmonary diseases. In this work we propose a deep CNN-RNN model t...
BACKGROUND: Interstitial lung disease requires frequent re-examination, which directly causes excessive cumulative radiation exposure. To date, AI has not been applied to CT for enhancing clinical care; thus, we hypothesize AI may empower CT with int...
Circulation. Arrhythmia and electrophysiology
32536204
BACKGROUND: Pulmonary vein isolation (PVI) is an effective treatment strategy for patients with atrial fibrillation (AF), but many experience AF recurrence and require repeat ablation procedures. The goal of this study was to develop and evaluate a m...
Journal of cardiovascular medicine (Hagerstown, Md.)
32332378
AIM: A validated algorithm for automatic aortic arch measurements in aortic coarctation (CoA) patients could standardize procedures for clinical planning.
The convergence of artificial intelligence (AI) and precision medicine promises to revolutionize health care. Precision medicine methods identify phenotypes of patients with less-common responses to treatment or unique healthcare needs. AI leverages ...
Cardiovascular engineering and technology
33179176
PURPOSE: We accelerate a pathline-based cardiovascular model building method by training machine learning models to directly predict vessel lumen surface points from computed tomography (CT) and magnetic resonance (MR) medical image data.
An individualized innovative disease management is of great importance for people with multiple sclerosis (pwMS) to cope with the complexity of this chronic, multidimensional disease. However, an individual state of the art strategy, with precise adj...
Radiogenomics uses machine-learning (ML) to directly connect the morphologic and physiological appearance of tumors on clinical imaging with underlying genomic features. Despite extensive growth in the area of radiogenomics across many cancers, and i...
BACKGROUND: Predicting outcome after aneurysmal subarachnoid hemorrhage (aSAH) is known to be challenging and complex. Machine learning approaches, of which feedforward artificial neural networks (ffANNs) are the most widely used, could contribute to...
Osteoporosis is a global health problem for ageing populations. The goals of osteoporosis treatment are to improve bone mineral density (BMD) and prevent fractures. One major obstacle that remains a great challenge to achieve the goals is how to sele...