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Chronic Disease

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Clinical Validation and Extension of an Automated, Deep Learning-Based Algorithm for Quantitative Sinus CT Analysis.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Sinus CT is critically important for the diagnosis of chronic rhinosinusitis. While CT is sensitive for detecting mucosal disease, automated methods for objective quantification of sinus opacification are lacking. We describe ...

A comparison of general and disease-specific machine learning models for the prediction of unplanned hospital readmissions.

Journal of the American Medical Informatics Association : JAMIA
Unplanned hospital readmissions are a burden to patients and increase healthcare costs. A wide variety of machine learning (ML) models have been suggested to predict unplanned hospital readmissions. These ML models were often specifically trained on ...

The effects of robot-assisted left-hand training on hemispatial neglect in older patients with chronic stroke: A pilot and randomized controlled trial.

Medicine
BACKGROUND: Even though a variety of rehabilitative technique have been implemented to ameliorate neglect symptoms of patients with stoke, the effects of limb activation using a robotic device are still unknown. The purpose of this study was to inves...

Constipation Predominant Irritable Bowel Syndrome and Functional Constipation Are Not Discrete Disorders: A Machine Learning Approach.

The American journal of gastroenterology
INTRODUCTION: Chronic constipation is classified into 2 main syndromes, irritable bowel syndrome with constipation (IBS-C) and functional constipation (FC), on the assumption that they differ along multiple clinical characteristics and are plausibly ...

The toll of noninfected CRS patients to the COVID-19 pandemic.

Rhinology
Social distancing with the aim of avoiding infections and pre-serve critical care capacities during the COVID-19 pandemic has been implemented in Germany according to World Health Organization (WHO) recommendations from early March onwards. Limitatio...

Machine Learning and Deep Neural Network Applications in the Thorax: Pulmonary Embolism, Chronic Thromboembolic Pulmonary Hypertension, Aorta, and Chronic Obstructive Pulmonary Disease.

Journal of thoracic imaging
The radiologic community is rapidly integrating a revolution that has not fully entered daily practice. It necessitates a close collaboration between computer scientists and radiologists to move from concepts to practical applications. This article r...

Role of Instruction Adherence During Highly Structured Robotic Arm Training on Motor Outcomes for Individuals After Chronic Stroke.

American journal of physical medicine & rehabilitation
The aim of this study was to examine the effects of instruction adherence on upper limb motor outcomes after highly structured intervention. A secondary data analysis was completed using mixed linear modeling design. Thirty chronic stroke survivors w...

Hand motion analysis during robot-aided rehabilitation in chronic stroke.

Journal of biological regulators and homeostatic agents
A high percentage of post-stroke patients reports spasticity and no functional use of the upper limb. To adapt the therapy in the most patient-specific manner, it is of paramount importance to objectively assess motor improvement during rehabilitatio...

Detection and Classification of Chronic Total Occlusion lesions using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Cardiovascular disease (CVD) is one of the diseases with the highest mortality rate in modern society, while chronic total occlusion (CTO) is the initial factor that influences the success rate of percutaneous coronary intervention (PCI), which is on...