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المؤلفN, Mishahira
المؤلفNair, Gayathri Geetha
المؤلفHoukan, Mohammad Talal
المؤلفSadasivuni, Kishor Kumar
المؤلفGeetha, Mithra
المؤلفAl-Maadeed, Somaya
المؤلفAlbusaidi, Asiya
المؤلفSubramanian, Nandhini
المؤلفYalcin, Huseyin Cagatay
المؤلفOuakad, Hassen M.
المؤلفBahadur, Issam
تاريخ الإتاحة2023-04-30T08:00:08Z
تاريخ النشر2022-11-19
اسم المنشورAdvancements in Smart, Secure and Intelligent Computing (ASSIC)
المعرّفhttp://dx.doi.org/10.1109/ASSIC55218.2022.10088409
الاقتباسM. N et al., "A New Deep Learning Method for Accurate Cardiac Heart Failure Prediction from RR Interval Measurements," 2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC), Bhubaneswar, India, 2022, pp. 1-7, doi: 10.1109/ASSIC55218.2022.10088409.
الترقيم الدولي الموحد للكتاب 978-1-6654-6110-8
معرّف المصادر الموحدhttp://hdl.handle.net/10576/42150
الملخصcardiovascular diseases are the major cause of death worldwide. Early detection of heart failure will assist patients and medical professionals in taking better precautions to reduce risks. The objective of this study is to find a technique that can reliably forecast the risk of cardiovascular illnesses. With the help of the training data we offer, deep learning algorithms like Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), and Recurrent Neural Network (RNN) make these predictions. Prediction accuracy will be reduced by a lack of medical data. As a part of our study, we examined DNN architectures to forecast cardiac failure. Over the training data, existing deep learning methods were employed. A new deep learning method that can predict heart failure using RR interval measurements is developed by comparing the accuracy performance of the proposed and existing models. The Physiobank NSR-RR and CHF-RR databases were used to compile the findings. The new model, which was based on experimental findings using these two free RR interval databases, attained a 94% accuracy rate compared to the existing model's 93.1% accuracy rate.
راعي المشروعQatar University IRCC program
اللغةen
الناشرIEEE
الموضوعHeart Failure
Deep learning
Time series
TimeLeNet. Database
العنوانA New Deep Learning Method for Accurate Cardiac Heart Failure Prediction from RR Interval Measurements
النوعConference Paper
الصفحات1-7
الترقيم الدولي الموحد للكتاب (إلكتروني) 978-1-6654-6109-2
dc.accessType Full Text


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