A novel method for determining postmortem interval based on the metabolomics of multiple organs combined with ensemble learning techniques.
Int J Legal Med
; 137(1): 237-249, 2023 Jan.
Article
de En
| MEDLINE
| ID: mdl-35661238
ABSTRACT
Determining postmortem interval (PMI) is one of the most challenging and essential endeavors in forensic science. Developments in PMI estimation can take advantage of machine learning techniques. Currently, applying an algorithm to obtain information on multiple organs and conducting joint analysis to accurately estimate PMI are still in the early stages. This study aimed to establish a multi-organ stacking model that estimates PMI by analyzing differential compounds of four organs in rats. In a total of 140 rats, skeletal muscle, liver, lung, and kidney tissue samples were collected at each time point after death. Ultra-performance liquid chromatography coupled with high-resolution mass spectrometry was used to determine the compound profiles of the samples. The original data were preprocessed using multivariate statistical analysis to determine discriminant compounds. In addition, three interrelated and increasingly complex patterns (single organ optimal model, single organ stacking model, multi-organ stacking model) were established to estimate PMI. The accuracy and generalized area under the receiver operating characteristic curve of the multi-organ stacking model were the highest at 93% and 0.96, respectively. Only 1 of the 14 external validation samples was misclassified by the multi-organ stacking model. The results demonstrate that the application of the multi-organ combination to the stacking algorithm is a potential forensic tool for the accurate estimation of PMI.
Mots clés
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Sujet principal:
Modifications postmortem
/
Métabolomique
Type d'étude:
Prognostic_studies
Limites:
Animals
Langue:
En
Journal:
Int J Legal Med
Sujet du journal:
JURISPRUDENCIA
Année:
2023
Type de document:
Article