ArticleInternational journal of legal medicine2020
Novel insights into wound age estimation: combined with "up, no change, or down" system and cosine similarity in python environment.
Article in International journal of legal medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 14 citations in OpenAlex.
- Combined metabolomics and tandem machine-learning models for wound age estimation: a novel analytical strategy.Forensic sciences research · 2023Article
- 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
- Estimating the time of skeletal muscle contusion based on the spatial distribution of neutrophils: a practical approach to forensic problems.International journal of legal medicine · 2022Article
- Screening criteria of mRNA indicators for wound age estimation.Forensic sciences research · 2022Article
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Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wound age estimation is a complex, multifactorial issue. It is considered to have great practical significance that combining multi-biomarkers and multi-methods for injury time estimation. We optimized our earlier "up, no change, or down" model by adding data on the expression levels of mRNAs encoding ABHD2, MAD2L2, and ARID5A, and we converted the relative quantitative expression levels of seven genes into a vector rather than a color model. We used Python to derive the cosine similarity (CS) between a test set and the vector matrix; the highest similarity most accurately reflected the injury time. For the optimized model, the internal and external verifications were approximately 0.71 and 0.66, respectively. The good double-blinded results indicated that the model was stable and reliable. In summary, we used a vector matrix and cosine similarities derived by Python to mine the levels of genes expressed in contused skeletal muscle. We are the first to combine several biomarkers and methods for wound age estimation.
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Registered trials
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