基于深度学习的2019冠状病毒病病死率爆发趋势

Q3 Medicine

International Journal of Medical Engineering and Informatics Pub Date : 2023-01-01 DOI:10.1504/ijmei.2023.127256

Robin Singh Bhadoria, Yash Gupta, Ivan Perl

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引用次数: 1

摘要

世界卫生组织(世卫组织)于2020年3月11日宣布新型冠状病毒为全球大流行。据悉，它起源于中国武汉，由于没有适当的药物和疫苗，它的传播无法阻挡。所开发的预测模型预测了新型冠状病毒病(COVID-19)的病例数和病死率，这是一种高度冲动性的疾病。本文提供了利用深度学习进行基于时间序列的预测的内在算法，即线性回归和长短期记忆(LSTM)。它还使用ReLU激活函数和Adam优化器。本文还对世界各大洲现有的COVID-19病例模型进行了比较研究。它还提供了一个广泛的模型，对2021年1月之前的病例数、康复时间、活跃时间和死亡率进行了简要预测。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Outbreak trends of fatality rate into coronavirus disease-2019 using deep learning

The World Health Organization (WHO) has declared the novel coronavirus as global pandemic on 11 March 2020. It was known to originate from Wuhan, China and its spread is unstoppable due to no proper medication and vaccine. The developed forecasting models predict the number of cases and its fatality rate for coronavirus disease 2019 (COVID-19), which is highly impulsive. This paper provides intrinsic algorithms namely - linear regression and long short-term memory (LSTM) using deep learning for time series-based prediction. It also uses the ReLU activation function and Adam optimiser. This paper also reports a comparative study on existing models for COVID-19 cases from different continents in the world. It also provides an extensive model that shows a brief prediction about the number of cases and time for recovered, active and deaths rate till January 2021.

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来源期刊

International Journal of Medical Engineering and Informatics Medicine-Medicine (miscellaneous)

CiteScore

2.20

自引率

0.00%

发文量

110

期刊介绍： IJMEI promotes an understanding of the structural/functional aspects of disease mechanisms and the application of technology towards the treatment/management of such diseases. It seeks to promote interdisciplinary collaboration between those interested in the theoretical and clinical aspects of medicine and to foster the application of computers and mathematics to problems arising from medical sciences. IJMEI includes authoritative review papers, the reporting of original research, and evaluation reports of new/existing techniques and devices. Each issue also contains a comprehensive information service. Topics covered include Hospital information/medical record systems, data protection/privacy Disease modelling/analysis, evidence-based clinical modelling/studies Computer-based patient/disease management systems Clinical trials/studies, outcome-based studies/analysis Electronic patient monitoring systems Nanotechnology in medicine, medical applications Tissue engineering, artificial organs, biomaterials design Healthcare standards, service standardisation Controlled medical terminology/vocabularies Nursing informatics, systems integration Healthcare/hospital management, economics Medical technology, intelligent instrumentation, telemedicine Medical/molecular imaging, disease management Bioinformatics, human genome studies/analysis Drug design.