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A conformal regressor for predicting negative conversion time of Omicron patients

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Abstract

In light of the situation and the characteristics of Omicron, the country has continuously optimized the rules for the prevention and control of COVID-19. The global epidemic is still spreading, and new cases of infection continue to emerge in China. To facilitate the infected person to estimate the course of virus infection, a prediction model for predicting negative conversion time is proposed in this article. The clinical features of Omicron-infected patients in Shandong Province in the first half of 2022 are retrospectively studied. These features are grouped by disease diagnosis result, clinical sign, traditional Chinese medicine symptoms, and drug use. These features are input to the eXtreme Gradient Boosting (XGBoost) model, and the output is the predicted number of negative conversion days. At the same time, XGBoost is used as the underlying algorithm of the conformal prediction (CP) framework, which can realize the probability interval estimation with a controllable error rate. The results show that the proposed model has a mean absolute error of 3.54 days and has the shortest interval prediction result. This shows that the method in this paper can carry more decision-making information and help people better understand the disease and self-estimate the course of the disease to a certain extent.

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Funding

This work is supported by the Introduction and Cultivation Program for Young Creative Talents in Colleges and Universities of Shandong Province (No. 2019–173) and the Natural Science Foundation of Shandong Province (No. ZR2020KF013, No. ZR2020QF043, No. ZR2022QG051, No. ZR2023QF094).

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Author notes

  1. Pingping Wang and Shenjing Wu contributed equally to this work.

Authors and Affiliations

  1. Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao, 266112, China

    Pingping Wang, Shenjing Wu, Kunmeng Liu, Jinyu Cong & Benzheng Wei

  2. Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, 266112, China

    Pingping Wang, Shenjing Wu, Kunmeng Liu, Jinyu Cong & Benzheng Wei

  3. Affiliated Hospital of Shandong University of Chinese Medicine, Jinan, 250011, China

    Mei Tian & Wei Zhang

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  1. Pingping Wang
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Correspondence to Wei Zhang or Benzheng Wei.

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Wang, P., Wu, S., Tian, M. et al. A conformal regressor for predicting negative conversion time of Omicron patients. Med Biol Eng Comput (2024). https://doi.org/10.1007/s11517-024-03029-8

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