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Prediction of Pulmonary to Systemic Flow Ratio in Patients With Congenital Heart Disease Using Deep Learning-Based Analysis of Chest Radiographs.

JAMA cardiology
IMPORTANCE: Chest radiography is a useful noninvasive modality to evaluate pulmonary blood flow status in patients with congenital heart disease. However, the predictive value of chest radiography is limited by the subjective and qualitive nature of ...

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...

Multiple Plasma Biomarkers for Risk Stratification in Patients With Heart Failure and Preserved Ejection Fraction.

Journal of the American College of Cardiology
BACKGROUND: Better risk stratification strategies are needed to enhance clinical care and trial design in heart failure with preserved ejection fraction (HFpEF).

Factors affecting the usability of an assistive soft robotic glove after stroke or multiple sclerosis.

Journal of rehabilitation medicine
OBJECTIVE: To explore the usability and effects of an assistive soft robotic glove in the home setting after stroke or multiple sclerosis.

Machine Learning Uncovers Food- and Excipient-Drug Interactions.

Cell reports
Inactive ingredients and generally recognized as safe compounds are regarded by the US Food and Drug Administration (FDA) as benign for human consumption within specified dose ranges, but a growing body of research has revealed that many inactive ing...

A Machine-Learning Approach to Predicting Smoking Cessation Treatment Outcomes.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
AIMS: Most cigarette smokers want to quit smoking and more than half make an attempt every year, but less than 10% remain abstinent for at least 6 months. Evidence-based tobacco use treatment improves the likelihood of quitting, but more than two-thi...

Investigating Predictors of Cognitive Decline Using Machine Learning.

The journals of gerontology. Series B, Psychological sciences and social sciences
OBJECTIVES: Genetic risks for cognitive decline are not modifiable; however their relative importance compared to modifiable factors is unclear. We used machine learning to evaluate modifiable and genetic risk factors for Alzheimer's disease (AD), to...

A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas.

Neuro-oncology
BACKGROUND: Isocitrate dehydrogenase (IDH) mutation status has emerged as an important prognostic marker in gliomas. Currently, reliable IDH mutation determination requires invasive surgical procedures. The purpose of this study was to develop a high...