{"id":166606,"date":"2025-01-20T16:35:21","date_gmt":"2025-01-20T15:35:21","guid":{"rendered":"https:\/\/stratec-med.com\/literatur\/deep-learning-in-sex-estimation-from-a-peripheral-quantitative-computed-tomography-scan-of-the-fourth-lumbar-vertebra-a-proof-of-concept-study-2\/"},"modified":"2025-01-20T16:35:22","modified_gmt":"2025-01-20T15:35:22","slug":"deep-learning-in-sex-estimation-from-a-peripheral-quantitative-computed-tomography-scan-of-the-fourth-lumbar-vertebra-a-proof-of-concept-study-2","status":"publish","type":"literatur","link":"https:\/\/stratec-med.com\/en\/literature\/deep-learning-in-sex-estimation-from-a-peripheral-quantitative-computed-tomography-scan-of-the-fourth-lumbar-vertebra-a-proof-of-concept-study-2\/","title":{"rendered":"Deep learning in sex estimation from a peripheral quantitative computed  tomography scan of the fourth lumbar vertebra-a proof-of-concept study."},"content":{"rendered":"<p>Sex estimation is a key element in the analysis of unknown skeletal remains. The  vertebrae display clear sex discrepancy and have proven accurate in conventional  morphometric sex estimation. This proof-of-concept study aimed to investigate the  possibility to develop a deep learning algorithm for sex estimation even from a  single peripheral quantitative computed tomography (pQCT) slice of the fourth  lumbar vertebra (L4). The study utilized a total of 117 vertebrae from the Terry  Anatomical Collection. There were 58 male and 59 female cadavers, all of the  white ethnicity, with the average age at death 49 years and a range of 24 to  77 years. A coronal pQCT scan was taken from the midway of the L4 corpus. Sex  estimation was performed in a total of 19 neural network architectures  implemented in the AIDeveloper software. Of the explored architectures, a  LeNet5-based algorithm reached the highest accuracy of 86.4% in the test set.  Sex-specific classification rates were 90.9% among males and 81.8% among females.  This preliminary finding advances the field by encouraging and directing future  research on artificial intelligence-based methods in sex estimation from  individual skeletal traits such as the vertebrae. Combining quickly obtained  imaging data with automated deep learning algorithms may establish a valuable  pipeline for forensic anthropology and provide aid when combined with traditional  methods.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Sex estimation is a key element in the analysis of unknown skeletal remains. The vertebrae display clear sex discrepancy and<\/p>\n","protected":false},"author":22,"parent":0,"menu_order":0,"template":"","format":"standard","meta":{"_acf_changed":false},"tags":[],"thema":[],"produktgruppe":[5825],"literatur_kategorie":[7213],"class_list":["post-166606","literatur","type-literatur","status-publish","format-standard","hentry","produktgruppe-pqct-en","literatur_kategorie-scientific-publications"],"acf":[],"_links":{"self":[{"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/literatur\/166606","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/literatur"}],"about":[{"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/types\/literatur"}],"author":[{"embeddable":true,"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/users\/22"}],"version-history":[{"count":0,"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/literatur\/166606\/revisions"}],"wp:attachment":[{"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/media?parent=166606"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/tags?post=166606"},{"taxonomy":"thema","embeddable":true,"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/thema?post=166606"},{"taxonomy":"produktgruppe","embeddable":true,"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/produktgruppe?post=166606"},{"taxonomy":"literatur_kategorie","embeddable":true,"href":"https:\/\/stratec-med.com\/en\/wp-json\/wp\/v2\/literatur_kategorie?post=166606"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}