LSTM Model for Prediction of Heart Failure in Big Data

The combination of big data and deep learning is a world-shattering technology that can make a great impact on any industry if used in a proper way. With the availability of large volume of health care datasets and progressions in deep learning techniques, systems are now well equipped in diagnosing...

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Veröffentlicht in:	Journal of medical systems Jg. 43; H. 5; S. 111 - 13
Hauptverfasser:	Maragatham, G, Devi, Shobana
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Springer Nature B.V 01.05.2019
Schlagworte:	Big Data Congestive heart failure Cost analysis Data management Deep Learning Diagnosis Electronic health records Electronic Health Records - organization & administration Electronic medical records Failure detection Feasibility studies Health care Health problems Heart Heart failure Heart Failure - diagnosis Heart Failure - diagnostic imaging Humans Long short-term memory Machine learning Mathematical models Neural networks Neural Networks, Computer Optimization Performance prediction Progressions Regularization Weight Long short-term memory Electronic health record LSTM Model Recurrent neural systems
ISSN:	0148-5598, 1573-689X, 1573-689X
Online-Zugang:	Volltext
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