{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T19:41:44Z","timestamp":1777923704894,"version":"3.51.4"},"reference-count":25,"publisher":"SAGE Publications","issue":"9","license":[{"start":{"date-parts":[[2023,11,1]],"date-time":"2023-11-01T00:00:00Z","timestamp":1698796800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Metabolic Syndrome and Related Disorders"],"published-print":{"date-parts":[[2023,11]]},"abstract":"<jats:sec>\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>Current evidence regarding the safety of abdominal subcutaneous injections in pregnant women is limited. In this study, we developed a predictive model for abdominal skin\u2013subcutaneous fat thickness (S-ScFT) by gestational periods (GP) in pregnant women.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>A total of 354 cases were measured for S-ScFT. Three machine learning algorithms, namely deep learning, random forest, and support vector machine, were used for S-ScFT predictive modeling and factor analysis for each abdominal site. Data analysis was performed using SPSS and RapidMiner softwares.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>The deep learning algorithm best predicted the abdominal S-ScFT. The common important variables in all three algorithms for the prediction of abdominal S-ScFT were menarcheal age, prepregnancy weight, prepregnancy body mass index (categorized), large fetus for gestational age, and alcohol consumption.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>Predicting the safety of subcutaneous injections during pregnancy could be beneficial for managing gestational diabetes mellitus in pregnant women.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1089\/met.2023.0043","type":"journal-article","created":{"date-parts":[[2023,9,5]],"date-time":"2023-09-05T11:21:22Z","timestamp":1693912882000},"page":"479-488","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Machine Learning-Based Prediction of Abdominal Subcutaneous Fat Thickness During Pregnancy"],"prefix":"10.1177","volume":"21","author":[{"given":"Moon Sook","family":"Hwang","sequence":"first","affiliation":[{"name":"College of Nursing, Woosuk University, Wanju, Republic of Korea."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eunjeong","family":"Song","sequence":"additional","affiliation":[{"name":"AI Convergence Education, College of Education, Dongguk University, Seoul, Republic of Korea."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8687-7561","authenticated-orcid":false,"given":"Jeonghee","family":"Ahn","sequence":"additional","affiliation":[{"name":"Department of Medicine, University of Ulsan College of Medicine, Seoul, Republic of Korea."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6156-1336","authenticated-orcid":false,"given":"Seungmi","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Nursing Science, Chungbuk National University, Chungbuk, Republic of Korea."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2023,11,15]]},"reference":[{"key":"e_1_3_5_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.diabres.2019.107843"},{"key":"e_1_3_5_3_2","doi-asserted-by":"publisher","DOI":"10.4093\/jkd.2015.16.3.174"},{"key":"e_1_3_5_4_2","unstructured":"Korean Society of Obstetrics and Gynecology. Obstetrics. 6th ed. Koonja Publishing Inc.: Paju; 2019."},{"key":"e_1_3_5_5_2","doi-asserted-by":"publisher","DOI":"10.1080\/17446651.2018.1476135"},{"key":"e_1_3_5_6_2","doi-asserted-by":"publisher","DOI":"10.5720\/kjcn.2017.22.3.207"},{"key":"e_1_3_5_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.phrs.2018.02.002"},{"key":"e_1_3_5_8_2","doi-asserted-by":"publisher","DOI":"10.1891\/1521-0987.15.4.160"},{"key":"e_1_3_5_9_2","unstructured":"Lori-Berard FD Donna H Gail M et al. Recommendations for Best Practice in Injection Technique. FIT Forum for Injection Technique: Canada; 2017:27."},{"key":"e_1_3_5_10_2","first-page":"i","article-title":"Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation","volume":"894","author":"World Health Organization","year":"2000","unstructured":"World Health Organization. Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation. World Health Organ Tech Rep Ser, 2000; 894:i-xii, 1\u2013253.","journal-title":"World Health Organ Tech Rep Ser"},{"key":"e_1_3_5_11_2","doi-asserted-by":"publisher","DOI":"10.7570\/jomes.2019.28.1.40"},{"key":"e_1_3_5_12_2","doi-asserted-by":"publisher","DOI":"10.4069\/kjwhn.2021.12.12"},{"key":"e_1_3_5_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.orcp.2017.10.003"},{"key":"e_1_3_5_14_2","doi-asserted-by":"publisher","DOI":"10.1111\/aogs.13486"},{"key":"e_1_3_5_15_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2018-023014"},{"key":"e_1_3_5_16_2","doi-asserted-by":"publisher","DOI":"10.1185\/03007995.2010.481203"},{"key":"e_1_3_5_17_2","doi-asserted-by":"publisher","DOI":"10.1111\/ajd.12177"},{"key":"e_1_3_5_18_2","doi-asserted-by":"publisher","DOI":"10.4093\/dmj.2014.38.2.120"},{"key":"e_1_3_5_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2019.07.007"},{"key":"e_1_3_5_20_2","doi-asserted-by":"publisher","DOI":"10.1023\/B:STCO.0000035301.49549.88"},{"key":"e_1_3_5_21_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2018.02.016"},{"key":"e_1_3_5_22_2","doi-asserted-by":"publisher","DOI":"10.5812\/ijem.16130"},{"key":"e_1_3_5_23_2","doi-asserted-by":"publisher","DOI":"10.2103\/7\/qims-21-370"},{"key":"e_1_3_5_24_2","doi-asserted-by":"publisher","DOI":"10.1111\/sms.13508"},{"issue":"1","key":"e_1_3_5_25_2","first-page":"16","article-title":"How drinking during pregnancy affects women's pregnancy weight gain and neonatal birth weights","volume":"15","author":"Kim EJ","year":"2011","unstructured":"Kim EJ, , Lee SH, , Shin SJ, et al. How drinking during pregnancy affects women's pregnancy weight gain and neonatal birth weights. J Korean Acad Addict Psychiatry, 2011; 15(1):16\u201321.","journal-title":"J Korean Acad Addict Psychiatry"},{"key":"e_1_3_5_26_2","unstructured":"Seoul National University Hospital. Fetal alcohol syndrome. SNUH; 2017. 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