Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Human skull has always been used for victim identification in forensic odontology. The gender-dimorphic bone of the skull is the mandible. The gonial angle has frequently been investigated for gender estimation with variable results and requires further exploration. We aim to compare the efficacy of gonial angle estimation by ancient methods of lateral cephalometric tracing compared with more recent digital analysis methods for gender estimation in the Indian population. Lateral cephalograms of 191 (96 M and 95F) cases above the age of 17 years were retrieved. Cephalometric analysis of gonial angle on radiographs was done using both manual cephalometric tracing method and digitally using Adobe Photoshop software. The results were subjected to statistical analysis for evaluation. The mean gonial angle was higher in females (125.05; 123.77 and 125.28) than in males (122.583; 121.715 and 122.008) using both manual and digital methods. On applying the logistical regression analysis (LRA), the digital method showed the highest gender estimation accuracy of 60.7% followed by Burstone's analysis (57.1%) and manual conventional analysis (56.5%). Burstone's analysis (57.9%) correctly identified increased females, whereas digital analysis (62.5%) and manual conventional analysis (59.4%) accurately recognised increased males. The present study showed a higher gender estimation accuracy using digital methods as compared to manual methods, but it still lacks the credibility to be used as a sole factor for predicting the gender of an individual. Hence, a cumulative factor must be taken into consideration for gender identification which would provide more promising results.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s12024-023-00625-2 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!