Artykuły w czasopismach na temat „ARRHYTHMIA DATABASE”
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CHIU, CHUANG-CHIEN, TONG-HONG LIN i BEN-YI LIAU. "USING CORRELATION COEFFICIENT IN ECG WAVEFORM FOR ARRHYTHMIA DETECTION". Biomedical Engineering: Applications, Basis and Communications 17, nr 03 (25.06.2005): 147–52. http://dx.doi.org/10.4015/s1016237205000238.
Pełny tekst źródłaZhai, Yuyun, Jinwei Li i Quan Zhang. "Network pharmacology and molecular docking analyses of the potential target proteins and molecular mechanisms underlying the anti-arrhythmic effects of Sophora Flavescens". Medicine 102, nr 30 (28.07.2023): e34504. http://dx.doi.org/10.1097/md.0000000000034504.
Pełny tekst źródłaDeal, Barbara J., Constantine Mavroudis, Jeffrey Phillip Jacobs, Melanie Gevitz i Carl Lewis Backer. "Arrhythmic complications associated with the treatment of patients with congenital cardiac disease: consensus definitions from the Multi-Societal Database Committee for Pediatric and Congenital Heart Disease". Cardiology in the Young 18, S2 (grudzień 2008): 202–5. http://dx.doi.org/10.1017/s104795110800293x.
Pełny tekst źródłaMoreland-Head, Lindsay N., James C. Coons, Amy L. Seybert, Matthew P. Gray i Sandra L. Kane-Gill. "Use of Disproportionality Analysis to Identify Previously Unknown Drug-Associated Causes of Cardiac Arrhythmias Using the Food and Drug Administration Adverse Event Reporting System (FAERS) Database". Journal of Cardiovascular Pharmacology and Therapeutics 26, nr 4 (6.01.2021): 341–48. http://dx.doi.org/10.1177/1074248420984082.
Pełny tekst źródłaZeng, Yuni, Hang Lv, Mingfeng Jiang, Jucheng Zhang, Ling Xia, Yaming Wang i Zhikang Wang. "Deep arrhythmia classification based on SENet and lightweight context transform". Mathematical Biosciences and Engineering 20, nr 1 (2022): 1–17. http://dx.doi.org/10.3934/mbe.2023001.
Pełny tekst źródłaKapoor, Ankita, Samarthkumar Thakkar, Lucas Battel, Harsh P. Patel, Nikhil Agrawal, Shipra Gandhi, Pritika Manaktala i in. "The Prevalence and Impact of Arrhythmias in Hospitalized Patients with Sickle Cell Disorders: A Large Database Analysis". Blood 136, Supplement 1 (5.11.2020): 5–6. http://dx.doi.org/10.1182/blood-2020-142099.
Pełny tekst źródłaOTHMAN, MOHD AFZAN, i NORLAILI MAT SAFRI. "CHARACTERIZATION OF VENTRICULAR ARRHYTHMIAS USING A SEMANTIC MINING ALGORITHM". Journal of Mechanics in Medicine and Biology 12, nr 03 (czerwiec 2012): 1250049. http://dx.doi.org/10.1142/s0219519412004946.
Pełny tekst źródłaXu, Gang, Guangxin Xing, Juanjuan Jiang, Jian Jiang i Yongsheng Ke. "Arrhythmia Detection Using Gated Recurrent Unit Network with ECG Signals". Journal of Medical Imaging and Health Informatics 10, nr 3 (1.03.2020): 750–57. http://dx.doi.org/10.1166/jmihi.2020.2928.
Pełny tekst źródłaN. S. V Rama Raju, N., V. Malleswara Rao i I. Srinivasa Rao. "Automatic detection and classification of cardiac arrhythmia using neural network". International Journal of Engineering & Technology 7, nr 3 (11.07.2018): 1482. http://dx.doi.org/10.14419/ijet.v7i3.14084.
Pełny tekst źródłaHerman, Jeffrey N., Richard I. Fogel, Philip J. Podrid i Gary R. Garber. "Entropy: A cardiac arrhythmia multimedia database". Journal of the American College of Cardiology 17, nr 2 (luty 1991): A10. http://dx.doi.org/10.1016/0735-1097(91)91008-3.
Pełny tekst źródłaUmapathi, Krishna Kishore, Aravind Thavamani, Harshitha Dhanpalreddy i Hoang H. Nguyen. "Prevalence of cardiac arrhythmias in cannabis use disorder related hospitalizations in teenagers from 2003 to 2016 in the United States". EP Europace 23, nr 8 (16.03.2021): 1302–9. http://dx.doi.org/10.1093/europace/euab033.
Pełny tekst źródłaGiriprasad Gaddam, P., A. Sanjeeva reddy i R. V. Sreehari. "Automatic Classification of Cardiac Arrhythmias based on ECG Signals Using Transferred Deep Learning Convolution Neural Network". Journal of Physics: Conference Series 2089, nr 1 (1.11.2021): 012058. http://dx.doi.org/10.1088/1742-6596/2089/1/012058.
Pełny tekst źródłaSoniwala, Mujtaba, Saadia Sherazi, Susan Schleede, Scott McNitt, Tina Faugh, Jeremiah Moore, Justin Foster i in. "Arrhythmia Burden in Patients with Indolent Lymphoma". Blood 136, Supplement 1 (5.11.2020): 6–7. http://dx.doi.org/10.1182/blood-2020-140053.
Pełny tekst źródłaHammad, Mohamed, Souham Meshoul, Piotr Dziwiński, Paweł Pławiak i Ibrahim A. Elgendy. "Efficient Lightweight Multimodel Deep Fusion Based on ECG for Arrhythmia Classification". Sensors 22, nr 23 (1.12.2022): 9347. http://dx.doi.org/10.3390/s22239347.
Pełny tekst źródłaKozieł, Paweł, Maria Grodkiewicz, Klaudia Artykiewicz, Kamila Gorczyca, Marcin Czarkowski, Aleksandra Słupczyńska, Weronika Urbaś, Klaudia Podgórska, Aleksandra Puła i Urszula Krzysiek. "Does the watch can detect cardiac arrhythmias?" Journal of Education, Health and Sport 13, nr 2 (8.01.2023): 293–98. http://dx.doi.org/10.12775/jehs.2023.13.02.042.
Pełny tekst źródłaDeCamilla, J., X. Xia, M. Wang, J. Wade, B. Mykins, W. Zareba i J. P. Couderc. "The multiple arrhythmia dataset evaluation database (M.A.D.A.E.)". Journal of Electrocardiology 51, nr 6 (listopad 2018): S106—S112. http://dx.doi.org/10.1016/j.jelectrocard.2018.08.005.
Pełny tekst źródłaLinghu, Rongqian, i Ke Zhang. "Real-time Automatic Arrhythmia Detection System based on Extreme Gradient Boosting and Neural Network Algorithm". Journal of Physics: Conference Series 2449, nr 1 (1.03.2023): 012033. http://dx.doi.org/10.1088/1742-6596/2449/1/012033.
Pełny tekst źródłaCintra, Fatima Dumas, Marcia Regina Pinho Makdisse, Wercules Antônio Alves de Oliveira, Camila Furtado Rizzi, Francisco Otávio de Oliveira Luiz, Sergio Tufik, Angelo Amato Vincenzo de Paola i Dalva Poyares. "Exercise-induced ventricular arrhythmias: analysis of predictive factors in a population with sleep disorders". Einstein (São Paulo) 8, nr 1 (marzec 2010): 62–67. http://dx.doi.org/10.1590/s1679-45082010ao1469.
Pełny tekst źródłaLiu, Feifei, Chengyu Liu, Xinge Jiang, Zhimin Zhang, Yatao Zhang, Jianqing Li i Shoushui Wei. "Performance Analysis of Ten Common QRS Detectors on Different ECG Application Cases". Journal of Healthcare Engineering 2018 (2018): 1–8. http://dx.doi.org/10.1155/2018/9050812.
Pełny tekst źródłaKhalaf, Akram Jaddoa, i Samir Jasim Mohammed. "Verification and comparison of MIT-BIH arrhythmia database based on number of beats". International Journal of Electrical and Computer Engineering (IJECE) 11, nr 6 (1.12.2021): 4950. http://dx.doi.org/10.11591/ijece.v11i6.pp4950-4961.
Pełny tekst źródłaLin, Shih-Yi, Wu-Huei Hsu, Cheng-Chieh Lin, Cheng-Li Lin, Chun-Hao Tsai, Chih-Hsueh Lin, Der-Cherng Chen, Tsung-Chih Lin, Chung-Y. Hsu i Chia-Hung Kao. "Association of Arrhythmia in Patients with Cervical Spondylosis: A Nationwide Population-Based Cohort Study". Journal of Clinical Medicine 7, nr 9 (23.08.2018): 236. http://dx.doi.org/10.3390/jcm7090236.
Pełny tekst źródłaAbdou, Abdoul-Dalibou, Ndeye Fatou Ngom i Oumar Niang. "Arrhythmias Prediction Using an Hybrid Model Based on Convolutional Neural Network and Nonlinear Regression". International Journal of Computational Intelligence and Applications 19, nr 03 (wrzesień 2020): 2050024. http://dx.doi.org/10.1142/s1469026820500248.
Pełny tekst źródłaBae, Tae Wuk, Sang Hag Lee i Kee Koo Kwon. "An Adaptive Median Filter Based on Sampling Rate for R-Peak Detection and Major-Arrhythmia Analysis". Sensors 20, nr 21 (29.10.2020): 6144. http://dx.doi.org/10.3390/s20216144.
Pełny tekst źródłaMoody, G. B., i R. G. Mark. "The impact of the MIT-BIH Arrhythmia Database". IEEE Engineering in Medicine and Biology Magazine 20, nr 3 (2001): 45–50. http://dx.doi.org/10.1109/51.932724.
Pełny tekst źródłaShen, Qin, Hongxiang Gao, Yuwen Li, Qi Sun, Minglong Chen, Jianqing Li i Chengyu Liu. "An Open-Access Arrhythmia Database of Wearable Electrocardiogram". Journal of Medical and Biological Engineering 40, nr 4 (22.07.2020): 564–74. http://dx.doi.org/10.1007/s40846-020-00554-3.
Pełny tekst źródłakamil, Sarah, i Lamia Muhammed. "Arrhythmia Classification Using One Dimensional Conventional Neural Network". International Journal of Advances in Soft Computing and its Applications 13, nr 3 (28.11.2021): 43–58. http://dx.doi.org/10.15849/ijasca.211128.04.
Pełny tekst źródłaMa, Shuai, Jianfeng Cui, Weidong Xiao i Lijuan Liu. "Deep Learning-Based Data Augmentation and Model Fusion for Automatic Arrhythmia Identification and Classification Algorithms". Computational Intelligence and Neuroscience 2022 (11.08.2022): 1–17. http://dx.doi.org/10.1155/2022/1577778.
Pełny tekst źródłaQin, Qin, Jianqing Li, Yinggao Yue i Chengyu Liu. "An Adaptive and Time-Efficient ECG R-Peak Detection Algorithm". Journal of Healthcare Engineering 2017 (2017): 1–14. http://dx.doi.org/10.1155/2017/5980541.
Pełny tekst źródłaHamarsheh, Qadri. "Autoregressive Modeling based ECG Cardiac Arrhythmias’ Database System". International Journal of Circuits, Systems and Signal Processing 16 (26.07.2022): 1074–83. http://dx.doi.org/10.46300/9106.2022.16.130.
Pełny tekst źródłaChintalapati, Usha Kumari, Md Aqeel Manzar, Tarun Varma N, Reethika A, Priya Samhitha B, Rohitha Sivani J, Kamran Ali Mirza i Pranav Kumar S. "Automated Detection of Depolarization and Repolarization of Cardiac Signal for Arrhythmia Classification". International Journal of Online and Biomedical Engineering (iJOE) 17, nr 02 (12.02.2021): 173. http://dx.doi.org/10.3991/ijoe.v17i02.18955.
Pełny tekst źródłaMathunjwa, Bhekumuzi M., Yin-Tsong Lin, Chien-Hung Lin, Maysam F. Abbod, Muammar Sadrawi i Jiann-Shing Shieh. "ECG Recurrence Plot-Based Arrhythmia Classification Using Two-Dimensional Deep Residual CNN Features". Sensors 22, nr 4 (20.02.2022): 1660. http://dx.doi.org/10.3390/s22041660.
Pełny tekst źródłaAnwar, Syed Muhammad, Maheen Gul, Muhammad Majid i Majdi Alnowami. "Arrhythmia Classification of ECG Signals Using Hybrid Features". Computational and Mathematical Methods in Medicine 2018 (12.11.2018): 1–8. http://dx.doi.org/10.1155/2018/1380348.
Pełny tekst źródłaZHANG, JIA-WEI, XIA LIU i JUN DONG. "CCDD: AN ENHANCED STANDARD ECG DATABASE WITH ITS MANAGEMENT AND ANNOTATION TOOLS". International Journal on Artificial Intelligence Tools 21, nr 05 (październik 2012): 1240020. http://dx.doi.org/10.1142/s0218213012400209.
Pełny tekst źródłaSoni, Ekta, Arpita Nagpal, Puneet Garg i Plácido Rogerio Pinheiro. "Assessment of Compressed and Decompressed ECG Databases for Telecardiology Applying a Convolution Neural Network". Electronics 11, nr 17 (29.08.2022): 2708. http://dx.doi.org/10.3390/electronics11172708.
Pełny tekst źródłaZhou, Haiying, Xiancheng Zhu, Sishan Wang, Kui Zhou, Zheng Ma, Jian Li, Kun-Mean Hou i Christophe De Vaulx. "A Novel Cardiac Arrhythmias Detection Approach for Real-Time Ambulatory ECG Diagnosis". International Journal of Pattern Recognition and Artificial Intelligence 31, nr 10 (9.03.2017): 1758004. http://dx.doi.org/10.1142/s0218001417580046.
Pełny tekst źródłaShadhon Chandra Mohonta i Md. Firoj Ali. "A Novel Approach to Detect Cardiac Arrhythmia Based on Continuous Wavelet Transform and Convolutional Neural Network". MIST INTERNATIONAL JOURNAL OF SCIENCE AND TECHNOLOGY 10 (29.12.2022): 37–41. http://dx.doi.org/10.47981/j.mijst.10(03)2022.341(37-41).
Pełny tekst źródłaQi, Meng, Hongxiang Shao, Nianfeng Shi, Guoqiang Wang i Yifei Lv. "Arrhythmia classification detection based on multiple electrocardiograms databases". PLOS ONE 18, nr 9 (27.09.2023): e0290995. http://dx.doi.org/10.1371/journal.pone.0290995.
Pełny tekst źródłaYan, Wei, i Zhen Zhang. "Online Automatic Diagnosis System of Cardiac Arrhythmias Based on MIT-BIH ECG Database". Journal of Healthcare Engineering 2021 (16.12.2021): 1–9. http://dx.doi.org/10.1155/2021/1819112.
Pełny tekst źródłaMeng, Yang, Guoxin Liang i Mei Yue. "Deep Learning-Based Arrhythmia Detection in Electrocardiograph". Scientific Programming 2021 (13.05.2021): 1–7. http://dx.doi.org/10.1155/2021/9926769.
Pełny tekst źródłaWang, Liang-Hung, Ze-Hong Yan, Yi-Ting Yang, Jun-Ying Chen, Tao Yang, I.-Chun Kuo, Patricia Angela R. Abu, Pao-Cheng Huang, Chiung-An Chen i Shih-Lun Chen. "A Classification and Prediction Hybrid Model Construction with the IQPSO-SVM Algorithm for Atrial Fibrillation Arrhythmia". Sensors 21, nr 15 (1.08.2021): 5222. http://dx.doi.org/10.3390/s21155222.
Pełny tekst źródłaXiao, Qiao, Khuan Lee, Siti Aisah Mokhtar, Iskasymar Ismail, Ahmad Luqman bin Md Pauzi, Qiuxia Zhang i Poh Ying Lim. "Deep Learning-Based ECG Arrhythmia Classification: A Systematic Review". Applied Sciences 13, nr 8 (14.04.2023): 4964. http://dx.doi.org/10.3390/app13084964.
Pełny tekst źródłaMANDAL, SAURAV, i NABANITA SINHA. "ARRHYTHMIA DIAGNOSIS FROM ECG SIGNAL ANALYSIS USING STATISTICAL FEATURES AND NOVEL CLASSIFICATION METHOD". Journal of Mechanics in Medicine and Biology 21, nr 03 (18.03.2021): 2150025. http://dx.doi.org/10.1142/s0219519421500251.
Pełny tekst źródłaSarshar, Nazanin Tataei, i Mohammad Mirzaei. "Premature Ventricular Contraction Recognition Based on a Deep Learning Approach". Journal of Healthcare Engineering 2022 (26.03.2022): 1–7. http://dx.doi.org/10.1155/2022/1450723.
Pełny tekst źródłaUllah, Wusat, Imran Siddique, Rana Muhammad Zulqarnain, Mohammad Mahtab Alam, Irfan Ahmad i Usman Ahmad Raza. "Classification of Arrhythmia in Heartbeat Detection Using Deep Learning". Computational Intelligence and Neuroscience 2021 (19.10.2021): 1–13. http://dx.doi.org/10.1155/2021/2195922.
Pełny tekst źródłaBen Itzhak, Sagi, Shir Sharony Ricon, Shany Biton, Joachim A. Behar i Jonathan A. Sobel. "Effect of temporal resolution on the detection of cardiac arrhythmias using HRV features and machine learning". Physiological Measurement 43, nr 4 (28.04.2022): 045002. http://dx.doi.org/10.1088/1361-6579/ac6561.
Pełny tekst źródłaWilly, Kevin, Julia Köbe, Florian Reinke, Benjamin Rath, Christian Ellermann, Julian Wolfes, Felix K. Wegner i in. "Usefulness of the MADIT-ICD Benefit Score in a Large Mixed Patient Cohort of Primary Prevention of Sudden Cardiac Death". Journal of Personalized Medicine 12, nr 8 (28.07.2022): 1240. http://dx.doi.org/10.3390/jpm12081240.
Pełny tekst źródłaYang, Xiong, Xin Yu Jin i Jian Feng Shen. "A PVC Identification Method of ECG Signal Based on Improved BPNN". Applied Mechanics and Materials 738-739 (marzec 2015): 578–81. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.578.
Pełny tekst źródłaIlbeigipour, Sadegh, Amir Albadvi i Elham Akhondzadeh Noughabi. "Real-Time Heart Arrhythmia Detection Using Apache Spark Structured Streaming". Journal of Healthcare Engineering 2021 (22.04.2021): 1–13. http://dx.doi.org/10.1155/2021/6624829.
Pełny tekst źródłaTejedor, Javier, David G. Marquez, Constantino A. Garcia i Abraham Otero. "A Tandem Feature Extraction Approach for Arrhythmia Identification". Electronics 10, nr 8 (19.04.2021): 976. http://dx.doi.org/10.3390/electronics10080976.
Pełny tekst źródłaSATHYAMANGALAM NATARAJAN, SHIVAPPRIYA, ARUN KUMAR SHANMUGAM, JUDE HEMANTH DURAISAMY i HARIKUMAR RAJAGURU. "PREDICTION OF CARDIAC ARRHYTHMIA USING MULTI CLASS CLASSIFIERS BY INCORPORATING WAVELET TRANSFORM BASED FEATURES". DYNA 97, nr 4 (1.07.2022): 418–24. http://dx.doi.org/10.6036/10458.
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