ArticleInternational journal of legal medicine2022
A preliminary study on early postmortem submersion interval (PMSI) estimation and cause-of-death discrimination based on nontargeted metabolomics and machine learning algorithms.
Article in International journal of legal medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Advances in postmortem interval estimation: A systematic review of machine learning and metabolomics across various tissue types.Forensic science, medicine, and pathology · 2025Pooled it
- PMI estimation with cross-species transfer learning and visual information generated by pathomics foundation model.International journal of legal medicine · 2026Article
- Molecular biology research progress in post-mortem interval (PMI) estimation in forensic medicine.International journal of legal medicine · 2026Review
- Article
- Estimation of postmortem interval under different ambient temperatures based on multi-organ metabolomics and machine learning algorithm.International journal of legal medicine · 2025Article
- A preliminary study on cause‑of‑death discrimination and the pathological stage identification in acute ischemia heart disease (AIHD) based on plasma lipidomic technique and machine learning algorithms.International journal of legal medicine · 2025Article
- Microbiota signature of the lung as the promising bioindicator for drowning diagnosis and postmortem submersion interval estimation.International journal of legal medicine · 2025Article
- Manner of death prediction: A machine learning approach to classify suicide and non-suicide using blood metabolomics.Forensic science international. Synergy · 2025Article
- Computer tomography-based radiomics combined with machine learning for predicting the time since onset of epidural hematoma.International journal of legal medicine · 2025Article
- Potential Biomarkers of Fatal Hypothermia Revealed by UHPLC-MS Metabolomics in Mice.Metabolites · 2025Article
- A computational approach to estimate postmortem interval using postmortem computed tomography of multiple tissues based on animal experiments.International journal of legal medicine · 2024Article
- The Role of Protein Degradation in Estimation Postmortem Interval and Confirmation of Cause of Death in Forensic Pathology: A Literature Review.International journal of molecular sciences · 2024Review
- Comparative analysis of anticoagulant influence on PMI estimation based on porcine blood metabolomics profile measured using GC-MS.Frontiers in molecular biosciences · 2024Article
- Novel Prediction Method Applied to Wound Age Estimation: Developing a Stacking Ensemble Model to Improve Predictive Performance Based on Multi-mRNA.Diagnostics (Basel, Switzerland) · 2023Article
- Postmortem submersion interval estimation of cadavers recovered from freshwater based on gut microbial community succession.Frontiers in microbiology · 2022Article
- Microbial communities in the liver and brain are informative for postmortem submersion interval estimation in the late phase of decomposition: A study in mouse cadavers recovered from freshwater.Frontiers in microbiology · 2022Article
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Authors and funding
10 authors.
Funding
Abstract
Postmortem submersion interval (PMSI) estimation and cause-of-death discrimination of corpses in water have long been challenges in forensic practice. Recently, many studies have linked postmortem metabolic changes with PMI extension, providing a potential strategy for estimating PMSI using the metabolome. Additionally, there is a lack of potential indicators with high sensitivity and specificity for drowning identification. In the present study, we profiled the untargeted metabolome of blood samples from drowning and postmortem submersion rats at different PMSIs within 24 h by liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 601 metabolites were detected. Four different machine learning algorithms, including random forest (RF), partial least squares (PLS), support vector machine (SVM), and neural network (NN), were used to compare the efficiency of the machine learning methods. Nineteen metabolites with obvious temporal regularity were selected as candidate biomarkers according to "IncNodePurity." Robust models were built with these biomarkers, which yielded a mean absolute error of 1.067 h. Additionally, 36 other metabolites were identified to build the classifier model for discriminating drowning and postmortem submersion (AUC = 1, accuracy = 95%). Our results demonstrated the potential application of metabolomics combined with machine learning in PMSI estimation and cause-of-death discrimination.
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