ArticleScientific reports2024
Identification of semen traces at a crime scene through Raman spectroscopy and machine learning.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Quantitative Determination of Prostate-Specific Antigen in Forensic Samples Using Antibody Microarrays on 3D Plasma Nanotextured Polymeric Slides.Sensors (Basel, Switzerland) · 2026Article
- Raman Spectroscopy of Cell-Free Cervicovaginal Lavage for HPV Lesion Diagnosis: A Pilot Study.International journal of molecular sciences · 2025Article
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Authors and funding
6 authors.
Funding
Abstract
Biological fluid stains can be instrumental in solving crimes. Identification of semen can help reconstruct events in sexual assault cases and identify suspects via DNA profiling. Current methods for semen identification suffer from limitations, including destruction of the sample and potential false positives. One of the main unsolved issues is the elimination of underlying substrate interference. In this paper, chemometric approaches were developed to isolate and identify a biofluid stain on interfering substrates using Raman spectroscopy. The first approach, called Multivariate Curve Resolution with the Addition Method, combines the standard addition method with multivariate curve resolution. The second one uses a criterion based on reducing the spectrum complexity when a spectral component is removed from a Raman spectrum of a multi-component sample entirely. The results demonstrate the superiority of the first approach relative to the second for both small volume fraction of the fluid stain compared to the substrate and random noise.
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Registered trials
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