{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:22:01Z","timestamp":1785802921332,"version":"3.56.0"},"reference-count":65,"publisher":"PeerJ","license":[{"start":{"date-parts":[[2023,11,22]],"date-time":"2023-11-22T00:00:00Z","timestamp":1700611200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Prince Sattam bin Abdulaziz University","award":["PSAU\/2023\/R\/1445"],"award-info":[{"award-number":["PSAU\/2023\/R\/1445"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>A common clinical method for identifying anomalies in bone growth in infants and newborns is skeletal age estimation with X-ray images. Children\u2019s bone abnormalities can result from several conditions including wounds, infections, or tumors. One of the most frequent reasons for bone issues is that most youngsters are affected by the slow displacement of bones caused by pressure applied to the growth plates as youngsters develop. The growth plate can be harmed by a lack of blood supply, separation from other parts of the bone, or slight misalignment. Problems with the growth plate prevent bones from developing, cause joint distortion, and may cause permanent joint injury. A significant discrepancy between the chronological and assessed ages may indicate a growth problem because determining bone age represents the real level of growth. Therefore, skeletal age estimation is performed to look for endocrine disorders, genetic problems, and growth anomalies. To address the bone age assessment challenge, this study uses the Radiological Society of North America\u2019s Pediatric Bone Age Challenge dataset which contains 12,600 radiological images of the left hand of a patient that includes the gender and bone age information. A bone age evaluation system based on the hand skeleton guidelines is proposed in this study for the detection of hand bone maturation. The proposed approach is based on a customized convolutional neural network. For the calculation of the skeletal age, different data augmentation techniques are used; these techniques not only increase the dataset size but also impact the training of the model. The performance of the model is assessed against the Visual Geometry Group (VGG) model. Results demonstrate that the customized convolutional neural network (CNN) model outperforms the VGG model with 97% accuracy.<\/jats:p>","DOI":"10.7717\/peerj-cs.1512","type":"journal-article","created":{"date-parts":[[2023,11,22]],"date-time":"2023-11-22T09:12:28Z","timestamp":1700644348000},"page":"e1512","source":"Crossref","is-referenced-by-count":9,"title":["Skeletal age evaluation using hand X-rays to determine growth problems"],"prefix":"10.7717","volume":"9","author":[{"given":"Muhammad","family":"Umer","sequence":"first","affiliation":[{"name":"Department of Computer Science & Information Technology, The Islamia University of Bahawalpur,  Bahawalpur, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ala\u2019 Abdulmajid","family":"Eshmawi","sequence":"additional","affiliation":[{"name":"Department of Cybersecurity, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Khaled","family":"Alnowaiser","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdullah","family":"Mohamed","sequence":"additional","affiliation":[{"name":"Research Centre, Future University in Egypt, New Cairo, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huda","family":"Alrashidi","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology and Computing, Arab Open University, Ardiya, Kuwait"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Imran","family":"Ashraf","sequence":"additional","affiliation":[{"name":"Information and Communication Engineering, Yeungnam University, Gyeongsan-si, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"4443","published-online":{"date-parts":[[2023,11,22]]},"reference":[{"issue":"2","key":"10.7717\/peerj-cs.1512\/ref-1","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.jbi.2004.01.002","article-title":"A computational TW3 classifier for skeletal maturity assessment. 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