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Heart Failure

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Congestive heart failure information extraction framework for automated treatment performance measures assessment.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This paper describes a new congestive heart failure (CHF) treatment performance measure information extraction system - CHIEF - developed as part of the Automated Data Acquisition for Heart Failure project, a Veterans Health Administration...

Individualized Knowledge Graph: A Viable Informatics Path to Precision Medicine.

Circulation research
We present here a vision of individualized Knowledge Graphs (iKGs) in cardiovascular medicine: a modern informatics platform of exchange and inquiry that comprehensively integrates biological knowledge with medical histories and health outcomes of in...

Using recurrent neural network models for early detection of heart failure onset.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We explored whether use of deep learning to model temporal relations among events in electronic health records (EHRs) would improve model performance in predicting initial diagnosis of heart failure (HF) compared to conventional methods th...

Prediction of 30-Day All-Cause Readmissions in Patients Hospitalized for Heart Failure: Comparison of Machine Learning and Other Statistical Approaches.

JAMA cardiology
IMPORTANCE: Several attempts have been made at developing models to predict 30-day readmissions in patients with heart failure, but none have sufficient discriminatory capacity for clinical use. Machine-learning (ML) algorithms represent a novel appr...

Soft robotic sleeve supports heart function.

Science translational medicine
There is much interest in form-fitting, low-modulus, implantable devices or soft robots that can mimic or assist in complex biological functions such as the contraction of heart muscle. We present a soft robotic sleeve that is implanted around the he...

PREDICTIVE MODELING OF HOSPITAL READMISSION RATES USING ELECTRONIC MEDICAL RECORD-WIDE MACHINE LEARNING: A CASE-STUDY USING MOUNT SINAI HEART FAILURE COHORT.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Reduction of preventable hospital readmissions that result from chronic or acute conditions like stroke, heart failure, myocardial infarction and pneumonia remains a significant challenge for improving the outcomes and decreasing the cost of healthca...

The Network Library: a framework to rapidly integrate network biology resources.

Bioinformatics (Oxford, England)
MOTIVATION: Much of the biological knowledge accumulated over the last decades is stored in different databases governed by various organizations and institutes. Integrating and connecting these vast knowledge repositories is an extremely useful meth...

Evaluation of periodic breathing in respiratory flow signal of elderly patients using SVM and linear discriminant analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aging population is a major concern that is reflected in the increase of chronic diseases. Heart Failure (HF) is one of the most common chronic diseases of elderly people that is punctuated with acute episodes, which result in hospitalization. The pe...

Length of Hospital Stay Prediction at the Admission Stage for Cardiology Patients Using Artificial Neural Network.

Journal of healthcare engineering
For hospitals' admission management, the ability to predict length of stay (LOS) as early as in the preadmission stage might be helpful to monitor the quality of inpatient care. This study is to develop artificial neural network (ANN) models to predi...