Sex Classification from Human Scent Using Image Interpretation of 2D Gas Chromatography-Mass Spectrometry Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00386496" target="_blank" >RIV/68407700:21230/25:00386496 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-95911-0_32" target="_blank" >https://doi.org/10.1007/978-3-031-95911-0_32</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-95911-0_32" target="_blank" >10.1007/978-3-031-95911-0_32</a>
Alternative languages
Result language
angličtina
Original language name
Sex Classification from Human Scent Using Image Interpretation of 2D Gas Chromatography-Mass Spectrometry Data
Original language description
Two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GCxGC ToF-MS) provides detailed chemical profiles of complex mixtures, making it useful in areas such as environmental monitoring and medical diagnostics. A promising application is sex classification from human scent, where subtle chemical differences indicate biological sex. In this paper, we propose a pattern recognition approach to sex classification that interprets raw GCxGC ToF-MS data as images, moving beyond traditional compound-based analysis. Our approach employs convolutional neural networks (CNNs) to analyze these images, and we compare its performance against established techniques – linear SVM, Ridge regression, and QDA – demonstrating robust and competitive results. Furthermore, we introduce and release a new dataset of GCxGC ToF-MS measurements to support reproducibility in future studies. Using an identity-aware cross-validation strategy, where test subjects are completely unseen during training, our method achieves approximately 88% accuracy on 504 measurements from 40 individuals.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Image Analysis
ISBN
978-3-031-95911-0
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
14
Pages from-to
457-470
Publisher name
Springer, Cham
Place of publication
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Event location
Reykjavik
Event date
Jun 23, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001553875500032