Optimized HSSE-GC-MS and machine learning for forensic gender classification of human scent from clothing

This integrated approach, combining optimized stir bar HSSE-GC-MS with different machine learning algorithms using the TIS untargeted approach, provides a fast and automatic gender classification from human scent traces on clothes that can be used as a rapid screening technique in forensic investigations to narrow down suspect or victim profiles.

Authors

Institutions

Publication Details

Journal
Analytica Chimica Acta
Published
2026-03-04
DOI
https://doi.org/10.1016/j.aca.2026.345337
Primary Topic
Forensic and Genetic Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimized HSSE-GC-MS and machine learning for forensic gender classification of human scent from clothing

John Marty Mateo, M. Ferreiro-González, Enrique Durán, José Luis P. Calle et al.
Analytica Chimica Acta
Forensic and Genetic Research
article

Optimized HSSE-GC-MS and machine learning for forensic gender classification of human scent from clothing

John Marty Mateo, M. Ferreiro-González, Enrique Durán, José Luis P. Calle, Miguel Palma
article en

Abstract

This integrated approach, combining optimized stir bar HSSE-GC-MS with different machine learning algorithms using the TIS untargeted approach, provides a fast and automatic gender classification from human scent traces on clothes that can be used as a rapid screening technique in forensic investigations to narrow down suspect or victim profiles.

Analytica Chimica ActaVol. 1400
Goethe University Frankfurt (DE), Universidad de Cádiz (ES)
Gender equality
Openalex Percentile: Top 35%
Forensic and Genetic Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.