Citations: Classification of normal sinus rhythm, abnormal arrhythmia and congestive heart failure ECG signals using LSTM and hybrid CNN-SVM deep neural networks

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Zihua Chen, Chuanli Wang, Huawei Jin, Jingzhao Li, Shunxiang Zhang & Qichun Ouyang. (2022) Hierarchical-fuzzy allocation and multi-parameter adjustment prediction for industrial loading optimisation. Connection Science 34:1, pages 687-708.
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Arvind Kumar, Nishant Sinha, Arpit Bhardwaj & Shivani Goel. (2022) Clinical risk assessment of chronic kidney disease patients using genetic programming. Computer Methods in Biomechanics and Biomedical Engineering 25:8, pages 887-895.
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Olga Shatalova, Sergey Filist, Nikolay Korenevskiy, Riad Taha Al-kasasbeh, Ashraf Shaqadan, Zeinab Protasova, Maksim Ilyash & Anatoly Rybochkin. (2021) Application of fuzzy neural network model and current-voltage analysis of biologically active points for prediction post-surgery risks. Computer Methods in Biomechanics and Biomedical Engineering 24:13, pages 1504-1516.
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Jagdeep Rahul, Marpe Sora, Lakhan Dev Sharma & Vijay Kumar Bohat. (2021) An improved cardiac arrhythmia classification using an RR interval-based approach. Biocybernetics and Biomedical Engineering.
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Pooja Sharma, Shail Kumar Dinkar & D. V. Gupta. (2021) A novel hybrid deep learning method with cuckoo search algorithm for classification of arrhythmia disease using ECG signals. Neural Computing and Applications.
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Ahmet Çınar & Seda Arslan Tuncer. (2021) Classification of lymphocytes, monocytes, eosinophils, and neutrophils on white blood cells using hybrid Alexnet-GoogleNet-SVM. SN Applied Sciences 3:4.
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Rahele Kafieh, Roya Arian, Narges Saeedizadeh, Zahra Amini, Nasim Dadashi Serej, Shervin Minaee, Sunil Kumar Yadav, Atefeh Vaezi, Nima Rezaei & Shaghayegh Haghjooy Javanmard. (2021) COVID-19 in Iran: Forecasting Pandemic Using Deep Learning. Computational and Mathematical Methods in Medicine 2021, pages 1-16.
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Classification of normal sinus rhythm, abnormal arrhythmia and congestive heart failure ECG signals using LSTM and hybrid CNN-SVM deep neural networks

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Classification of normal sinus rhythm, abnormal arrhythmia and congestive heart failure ECG signals using LSTM and hybrid CNN-SVM deep neural networks

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