Circulation journal : official journal of the Japanese Circulation Society
Oct 8, 2021
BACKGROUND: Radiofrequency catheter ablation (RFCA) is an effective therapy for atrial fibrillation (AF). However, it the problem of AF recurrence remains. This study investigates whether a deep convolutional neural network (CNN) can accurately predi...
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Aug 13, 2021
BACKGROUND: Chagas disease (CD) and ischemic stroke (IS) have a close, but poorly understood, association. There is paucity of evidence on the ideal secondary prophylaxis and etiological determination, with few cardioembolic patients being identified...
BACKGROUND: Surgical resection is the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC) and the survival of patients after radical resection is closely related to relapse. We aimed to develop models to predict the risk o...
Multiple sclerosis (MS) can be divided into four phenotypes based on clinical evolution. The pathophysiological boundaries of these phenotypes are unclear, limiting treatment stratification. Machine learning can identify groups with similar features ...
BACKGROUND: Renal flare of lupus nephritis (LN) is strongly associated with poor kidney outcomes, and predicting renal flare and stratifying its risk are important for clinical decision-making and individualized management to reduce LN flare.
OBJECTIVE: To investigate left atrial shape differences on CT scans of atrial fibrillation (AF) patients with (AF+) versus without (AF-) post-ablation recurrence and whether these shape differences predict AF recurrence.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mar 8, 2021
Recurrent angina (RA) after percutaneous coronary intervention (PCI) has few known risk factors, hampering the identification of high-risk populations. In this multicenter study, plasma samples are collected from patients with stable angina after PCI...
Annals of clinical and translational neurology
Feb 24, 2021
OBJECTIVE: No relapse risk prediction tool is currently available to guide treatment selection for multiple sclerosis (MS). Leveraging electronic health record (EHR) data readily available at the point of care, we developed a clinical tool for predic...
Disease relapse is the greatest cause of treatment failure in paediatric B-cell acute lymphoblastic leukaemia (B-ALL). Current risk stratifications fail to capture all patients at risk of relapse. Herein, we used a machine-learning approach to identi...
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