ArticleInternational journal of legal medicine2020
Sex estimation: a comparison of techniques based on binary logistic, probit and cumulative probit regression, linear and quadratic discriminant analysis, neural networks, and naïve Bayes classification using ordinal variables.
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 16 papers.
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Who cites it
16 citing papers in PubMed.
- Sex differences in hip bone and sacrum morphology: a geometric morphometric analysis.International journal of legal medicine · 2026Article
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- Evaluating the Effectiveness of Coxal Bone Measurements for Sex Estimation via Machine Learning.Biology · 2025Article
- Real-world application of Short Term Psychodynamic Psychotherapy (STPP) as chronic migraine preventive therapy: Profiling responders and predictive factors.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025Observational
- Sexual dimorphism of the humerus bones in a French sample: comparison of several statistical models including machine learning models.International journal of legal medicine · 2025Article
- Sex classification accuracy through machine learning algorithms - morphometric variables of human ear and nose.BMC research notes · 2025Article
- Sex determination based on features of the craniofacial bones in a sample of the central Chinese population using cone beam computed tomography.Forensic sciences research · 2025Article
- A statistical evaluation of the sexual dimorphism of the acetabulum in an Iberian population.International journal of legal medicine · 2025Article
- Deep learning versus human assessors: forensic sex estimation from three-dimensional computed tomography scans.Scientific reports · 2024Article
- Enhancing Sex Estimation Accuracy with Cranial Angle Measurements and Machine Learning.Biology · 2024Article
- Classification performance of the Sella-Tunis et al. (2017) sex estimation method in Czech population: different posterior probability threshold approaches.International journal of legal medicine · 2024Article
- Building gender-specific sexually transmitted infection risk prediction models using CatBoost algorithm and NHANES data.BMC medical informatics and decision making · 2024Article
- Sex estimation from long bones: a machine learning approach.International journal of legal medicine · 2023Article
- Boosting algorithm improves the accuracy of juvenile forensic dental age estimation in southern China population.Scientific reports · 2022Article
- Classifications of atherosclerotic plaque components with T1 and T2* mapping in 11.7 T MRI.European journal of radiology open · 2021Article
- Headspace Gas Chromatography Coupled to Mass Spectrometry and Ion Mobility Spectrometry: Classification of Virgin Olive Oils as a Study Case.Foods (Basel, Switzerland) · 2020Article
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2 authors.
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Abstract
The performance of seven classification methods, binary logistic (BLR), probit (PR) and cumulative probit (CPR) regression, linear (LDA) and quadratic (QDA) discriminant analysis, artificial neural networks (ANN), and naïve Bayes classification (NBC), is examined in skeletal sex estimation. These methods were tested using cranial and pelvic sexually dimorphic traits recorded on a modern documented collection, the Athens Collection. For their implementation, an R package has been written to perform cross-validated (CV) sex classification and give the discriminant function of each of the methods studied. A simple algorithm that combines two discriminant functions is also proposed. It was found that the differences in the classification performance between BLR, PR, CPR, LDA, QDA, ANN, and NBC are overall small. However, LDA is simpler and more flexible than CPR, QDA, and ANN and has a small but clear advantage over BLR, NBC, and PR. Consequently, LDA may be preferred in skeletal sex estimation. Finally, it is striking that the combination of pelvic and cranial traits via their discriminant functions, determined either by BLR or LDA, removes practically any population-specificity and yields much better predictions than the individual functions; in fact, the prediction accuracy increases above 97%.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.