An Automatic Approach Designed for Inference of the Underlying Cause-of-Death of Citizens

Ge, Hui; Gao, Keyan; Li, Shaoqiong; Wang, Wei; Chen, Qiang; Lin, Xialv; Huan, Ziyi; Su, Xuemei; Yang, Xu

doi:10.3390/ijerph18052414

Open AccessArticle

An Automatic Approach Designed for Inference of the Underlying Cause-of-Death of Citizens

by

Hui Ge

¹,

Keyan Gao

²

,

Shaoqiong Li

¹,

Wei Wang

¹,

Qiang Chen

¹,

Xialv Lin

²,

Ziyi Huan

²

,

Xuemei Su

^1,* and

Xu Yang

^2,*

¹

Chinese Center for Disease Control and Prevention, Beijing 102206, China

²

School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China

^*

Authors to whom correspondence should be addressed.

Int. J. Environ. Res. Public Health 2021, 18(5), 2414; https://doi.org/10.3390/ijerph18052414

Submission received: 12 January 2021 / Revised: 25 February 2021 / Accepted: 26 February 2021 / Published: 2 March 2021

(This article belongs to the Special Issue Simulations and Machine Learning via Big Data for Prediction, Detection, Treatment or Rehabilitation in the Healthcare Process)

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Abstract

It is very important to have a comprehensive understanding of the health status of a country’s population, which helps to develop corresponding public health policies. Correct inference of the underlying cause-of-death for citizens is essential to achieve a comprehensive understanding of the health status of a country’s population. Traditionally, this relies mainly on manual methods based on medical staff’s experiences, which require a lot of resources and is not very efficient. In this work, we present our efforts to construct an automatic method to perform inferences of the underlying causes-of-death for citizens. A sink algorithm is introduced, which could perform automatic inference of the underlying cause-of-death for citizens. The results show that our sink algorithm could generate a reasonable output and outperforms other stat-of-the-art algorithms. We believe it would be very useful to greatly enhance the efficiency of correct inferences of the underlying causes-of-death for citizens.

Keywords: cause-of-death inference; automatical; public heath; medical service

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MDPI and ACS Style

Ge, H.; Gao, K.; Li, S.; Wang, W.; Chen, Q.; Lin, X.; Huan, Z.; Su, X.; Yang, X. An Automatic Approach Designed for Inference of the Underlying Cause-of-Death of Citizens. Int. J. Environ. Res. Public Health 2021, 18, 2414. https://doi.org/10.3390/ijerph18052414

AMA Style

Ge H, Gao K, Li S, Wang W, Chen Q, Lin X, Huan Z, Su X, Yang X. An Automatic Approach Designed for Inference of the Underlying Cause-of-Death of Citizens. International Journal of Environmental Research and Public Health. 2021; 18(5):2414. https://doi.org/10.3390/ijerph18052414

Chicago/Turabian Style

Ge, Hui, Keyan Gao, Shaoqiong Li, Wei Wang, Qiang Chen, Xialv Lin, Ziyi Huan, Xuemei Su, and Xu Yang. 2021. "An Automatic Approach Designed for Inference of the Underlying Cause-of-Death of Citizens" International Journal of Environmental Research and Public Health 18, no. 5: 2414. https://doi.org/10.3390/ijerph18052414

APA Style

Ge, H., Gao, K., Li, S., Wang, W., Chen, Q., Lin, X., Huan, Z., Su, X., & Yang, X. (2021). An Automatic Approach Designed for Inference of the Underlying Cause-of-Death of Citizens. International Journal of Environmental Research and Public Health, 18(5), 2414. https://doi.org/10.3390/ijerph18052414

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An Automatic Approach Designed for Inference of the Underlying Cause-of-Death of Citizens

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