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01-05-2021 | Original Article

An efficient method for building a database of diatom populations for drowning site inference using a deep learning algorithm

Authors: Ji Zhang, Yuanyuan Zhou, Duarte Nuno Vieira, Yongjie Cao, Kaifei Deng, Qi Cheng, Yongzheng Zhu, Jianhua Zhang, Zhiqiang Qin, Kaijun Ma, Yijiu Chen, Ping Huang

Published in: International Journal of Legal Medicine | Issue 3/2021

Abstract

Seasonal or monthly databases of the diatom populations in specific bodies of water are needed to infer the drowning site of a drowned body. However, existing diatom testing methods are laborious, time-consuming, and costly and usually require specific expertise. In this study, we developed an artificial intelligence (AI)-based system as a substitute for manual morphological examination capable of identifying and classifying diatoms at the species level. Within two days, the system collected information on diatom profiles in the Huangpu and Suzhou Rivers of Shanghai, China. In an animal experiment, the similarities of diatom profiles between lung tissues and water samples were evaluated through a modified Jensen-Shannon (JS) divergence measure for drowning site inference, reaching a prediction accuracy of 92.31%. Considering its high efficiency and simplicity, our proposed method is believed to be more applicable than existing methods for seasonal or monthly water monitoring of diatom populations from sections of interconnected rivers, which would help police narrow the investigation scope to confirm the identity of an immersed body.

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Title: An efficient method for building a database of diatom populations for drowning site inference using a deep learning algorithm
Authors: Ji Zhang
Yuanyuan Zhou
Duarte Nuno Vieira
Yongjie Cao
Kaifei Deng
Qi Cheng
Yongzheng Zhu
Jianhua Zhang
Zhiqiang Qin
Kaijun Ma
Yijiu Chen
Ping Huang
Publication date: 01-05-2021
Publisher: Springer Berlin Heidelberg
Published in: International Journal of Legal Medicine / Issue 3/2021
Print ISSN: 0937-9827
Electronic ISSN: 1437-1596
DOI: https://doi.org/10.1007/s00414-020-02497-5

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An efficient method for building a database of diatom populations for drowning site inference using a deep learning algorithm

Abstract

Keynote webinar | Spotlight on sleep in brain health

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