Analysis and prediction of monkeypox confirmed cases using ARIMA and LSTM: a comparative study

Hanbei Xiong

doi:10.1117/12.2669383

24 March 2023 Analysis and prediction of monkeypox confirmed cases using ARIMA and LSTM: a comparative study

Hanbei Xiong

Proceedings Volume 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022); 126112D (2023) https://doi.org/10.1117/12.2669383
Event: International Conference on Biological Engineering and Medical Science (ICBioMed2022), 2022, Oxford, United Kingdom

Abstract

Monkeypox was identified as a disease of public health im- portance by World Health Organization. There is a monkeypox outbreak in U.S. and the rest of countries in the world. If cases can be anticipated in advance, appropriate precautions can be implemented promptly, reducing the damage caused by this pandemic. In this paper, predictions of the numbers of affected patients and daily increment across the world will be made. On the meantime, a comparative study on the model performance of Auto Regressive Integrated Moving Aver- age model (ARIMA) and RNN (Recurrent Neural Network) based LSTM (Long Short Term Memory) Model had been used.

Citation Download Citation

Hanbei Xiong "Analysis and prediction of monkeypox confirmed cases using ARIMA and LSTM: a comparative study", Proc. SPIE 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022), 126112D (24 March 2023); https://doi.org/10.1117/12.2669383

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