Strokes

A Stroke Risk Detection: Improving Hybrid Feature Selection Method.

BACKGROUND: Stroke is one of the most common diseases that cause mortality. Detecting the risk of stroke for individuals is critical yet challenging because of a large number of risk factors for stroke.

Causability and explainability of artificial intelligence in medicine.

Explainable artificial intelligence (AI) is attracting much interest in medicine. Technically, the problem of explainability is as old as AI itself and classic AI represented comprehensible retraceable approaches. However, their weakness was in dealing with uncertainties of the real world. Through the introduction of probabilistic learning, applications became increasingly successful, but increasi...

Development of an intelligent decision support system for ischemic stroke risk assessment in a population-based electronic health record database.

BACKGROUND: Intelligent decision support systems (IDSS) have been applied to tasks of disease management. Deep neural networks (DNNs) are artificial i...

Hybrid Rehabilitation Therapies on Upper-Limb Function and Goal Attainment in Chronic Stroke.

This study examined the treatment effects between unilateral hybrid therapy (UHT; unilateral robot-assisted therapy [RT] + modified constraint-induced...

Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke.

BACKGROUND AND PURPOSE: This project assessed performance of natural language processing (NLP) and machine learning (ML) algorithms for classification...

A Machine Learning Approach for Classifying Ischemic Stroke Onset Time From Imaging.

Current clinical practice relies on clinical history to determine the time since stroke (TSS) onset. Imaging-based determination of acute stroke onset...

Natural language processing of lifestyle modification documentation.

Lifestyle modification, including diet, exercise, and tobacco cessation, is the first-line treatment of many disorders including hypertension, obesity...

Rehab-Net: Deep Learning Framework for Arm Movement Classification Using Wearable Sensors for Stroke Rehabilitation.

In this paper, we present a deep learning framework "Rehab-Net" for effectively classifying three upper limb movements of the human arm, involving ext...

Patient-Level Prediction of Cardio-Cerebrovascular Events in Hypertension Using Nationwide Claims Data.

BACKGROUND: Prevention and management of chronic diseases are the main goals of national health maintenance programs. Previously widely used screening...

Using machine learning to optimize selection of elderly patients for endovascular thrombectomy.

BACKGROUND: Endovascular thrombectomy (ET) is the standard of care for treatment of acute ischemic stroke (AIS) secondary to large vessel occlusion. T...

Association Between Net Vertebral Artery Flow Volume and Non-AF Stroke: A Retrospective 2-Year Analysis.

Association between net vertebral artery flow volume (NVAFV) and stroke types remains unclear. We hypothesize NVAFV is low in patients with posterior...

A Large Animal Model of Right Ventricular Failure due to Chronic Thromboembolic Pulmonary Hypertension: A Focus on Function.

Chronic thromboembolic pulmonary hypertension (CTEPH) is a debilitating disease that progresses to right ventricular (RV) failure and death if left un...

Convolutional Neural Networks for Direct Inference of Pharmacokinetic Parameters: Application to Stroke Dynamic Contrast-Enhanced MRI.

The T1-weighted dynamic contrast enhanced (DCE)-MRI is an imaging technique that provides a quantitative measure of pharmacokinetic (PK) parameters c...

Postmarketing surveillance on clinical use of edoxaban in patients with nonvalvular atrial fibrillation (ETNA-AF-Japan): Three-month interim analysis results.

BACKGROUND: Direct oral anticoagulants are the first-line drugs for anticoagulation therapy in nonvalvular atrial fibrillation (NVAF). However, a real...

Radiomics-Based Intracranial Thrombus Features on CT and CTA Predict Recanalization with Intravenous Alteplase in Patients with Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: Thrombus characteristics identified on non-contrast CT (NCCT) are potentially associated with recanalization with intravenous ...

Correlation of the modified Medical Research Council dyspnea scale with airway structure assessed by three-dimensional CT in patients with chronic obstructive pulmonary disease.

BACKGROUND: Dyspnea is a common symptom in chronic obstructive pulmonary disease (COPD). The modified Medical Research Council (mMRC) dyspnea scale is...

Anticoagulant Related Nephropathy Induced by Dabigatran.

We describe a case of biopsy-proven dabigatran related nephropathy in a patient without underlying IgA nephropathy. To date, dabigatran related nephro...

Development and flight performance of a biologically-inspired tailless flapping-wing micro air vehicle with wing stroke plane modulation.

The tailless flapping-wing micro air vehicle (FW-MAV) is one of the most challenging problems in flapping-wing design due to its lack of tail for inhe...

Towards stroke prediction using electronic health records.

BACKGROUND: As of 2014, stroke is the fourth leading cause of death in Japan. Predicting a future diagnosis of stroke would better enable proactive fo...

Automated ASPECTS on Noncontrast CT Scans in Patients with Acute Ischemic Stroke Using Machine Learning.

BACKGROUND AND PURPOSE: Alberta Stroke Program Early CT Score (ASPECTS) was devised as a systematic method to assess the extent of early ischemic chan...