AUTHOR=Du Qiu-xiang , Zhang Shuai , Long Fei-hao , Lu Xiao-jun , Wang Liang , Cao Jie , Jin Qian-qian , Ren Kang , Zhang Ji , Huang Ping , Sun Jun-hong 

TITLE=Combining with lab-on-chip technology and multi-organ fusion strategy to estimate post-mortem interval of rat

JOURNAL=Frontiers in Medicine

VOLUME=Volume 9 - 2022

YEAR=2023

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2022.1083474

DOI=10.3389/fmed.2022.1083474

ISSN=2296-858X

ABSTRACT=Background: Post-mortem interval (PMI) estimation is one of the most important problems in forensic pathology all the time. Although many classical methods can be used to estimate time since death, accurate and rapid estimation of PMI is still a difficult task in forensic practice, so the estimation of PMI requires a faster, more accurate and more convenient method. 
Materials and methods: In this study, an experimental method, lab-on-chip, is used to analyze characterizations of polypeptide fragments of Lung, Liver, Kidney, and skeletal muscle of rats at defined time points after death (0d, 1d, 2d,3d, 5d, 7d, 9d, 12d, 15d, 18d, 21d, 24d, 27d, 30d). Then, machine learning algorithms (base model: LR, SVM, RF, GBDT, MLPC; ensemble model: stacking, soft voting, and soft weighted voting) are applied to predict PMI with single-organ. Multi-organ fusion strategy is designed to predict PMI based on multiple organs. Then, the ensemble pruning algorithm determines the best combination of multi-organ. 
Results: The Kidney is the best single organ for predicting the time of death, and its internal and external accuracy is 0.808 and 0.714, respectively. Multi-organ fusion strategy dramatically improves the performance of PMI estimation, and its internal and external accuracy is 0.962 and 0.893. Finally, the best organ combination determined by ensemble pruning algorithm is all organs: Lung, Liver, Kidney and skeletal muscle.