Computer methods and programs in biomedicine
Feb 6, 2020
BACKGROUND AND OBJECTIVE: Heart Failure is a clinical syndrome commonly caused by any structural or functional impairment. Fast and accurate mortality prediction for Heart Failure is essential to improve the health care of patients and prevent them f...
Discussed in this paper is the tip-over stability analysis of a pelvic support walking robot. To improve the activities of daily living (ADL) in hemiplegic patients, a pelvic support walking robot is proposed to help patients facilitating their rehab...
In recent years, the number of vulnerabilities discovered and publicly disclosed has shown a sharp upward trend. However, the value of exploitation of vulnerabilities varies for attackers, considering that only a small fraction of vulnerabilities are...
IMPORTANCE: The ability to accurately predict in-hospital mortality for patients at the time of admission could improve clinical and operational decision-making and outcomes. Few of the machine learning models that have been developed to predict in-h...
BMC medical informatics and decision making
Feb 3, 2020
BACKGROUND: Cardiovascular diseases kill approximately 17 million people globally every year, and they mainly exhibit as myocardial infarctions and heart failures. Heart failure (HF) occurs when the heart cannot pump enough blood to meet the needs of...
Computer methods and programs in biomedicine
Feb 1, 2020
INTRODUCTION: Being able to predict functional outcomes after a stroke is highly desirable for clinicians. This allows clinicians to set reasonable goals with patients and relatives, and to reach shared after-care decisions for recovery or rehabilita...
Because depression has high prevalence and cause enduring disability, it is important to predict onset of depression among community dwelling adults. In this study, we aimed to build a machine learning-based predictive model for future onset of depre...
To compare different deep learning architectures for predicting the risk of readmission within 30 days of discharge from the intensive care unit (ICU). The interpretability of attention-based models is leveraged to describe patients-at-risk. Several ...