{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T16:38:03Z","timestamp":1788194283894,"version":"build-2803163510"},"reference-count":42,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["THC"],"published-print":{"date-parts":[[2022,7,8]]},"abstract":"<jats:p>BACKGROUND: Timely and accurate diagnosis of genetic diseases can lead to proper action and prevention of irreparable events. OBJECTIVE: In this work we propose an integrated genetic-neural network (GNN) to improve the prediction risk of trisomy diseases including Down\u2019s syndrome (T21), Edwards\u2019 syndrome (T18) and Patau\u2019s Syndrome (T13). METHODS: A dataset including 561 pregnant were created. In this integrated model, the structure and input parameters of the proposed multilayer feedforward network (MFN) were optimized. RESULTS: The results of execution of the GNN on the testing dataset showed that the developed model can be accurately classify the anomalies from healthy fetus with 97.58% accuracy rate, and 99.44% and 85.65% sensitivity, and specificity, respectively. In the proposed GNN model, the Levenberg Merquident (LM) algorithm, the Radial Basis (Radbas) function from various types of functions were selected by the proposed GA. Moreover, maternal age, Nuchal Translucency (NT), Crown-rump length (CRL), Pregnancy-associated plasma protein A (PAPP-A) were selected by the proposed GA as the most effective factors for classifying the healthfetuses from the cases with fetal disorders. CONCLUSION: The proposed computerized model increases the diagnostic performance of the physicians especially in the accurate detection of healthy fetus with non \u2013 invasive and low \u2013 cost treatments.<\/jats:p>","DOI":"10.3233\/thc-213628","type":"journal-article","created":{"date-parts":[[2022,3,8]],"date-time":"2022-03-08T13:59:52Z","timestamp":1646747992000},"page":"951-965","source":"Crossref","is-referenced-by-count":5,"title":["A machine learning technology to improve the risk of non-invasive prenatal tests"],"prefix":"10.1177","volume":"30","author":[{"given":"Amir","family":"Jamshidnezhad","sequence":"first","affiliation":[{"name":"Fertility, Infertility and Perinatology Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran"},{"name":"Department of Health Information Technology, School of Allied Medical Sciences, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seyed Mohsen","family":"Hosseini","sequence":"additional","affiliation":[{"name":"Department of Health Information Technology, School of Allied Medical Sciences, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mandana","family":"Mahmudi","sequence":"additional","affiliation":[{"name":"Fertility, Infertility and Perinatology Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Javad","family":"Mohammadi-Asl","sequence":"additional","affiliation":[{"name":"Department of Medical Genetics, Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","reference":[{"issue":"6","key":"10.3233\/THC-213628_ref1","first-page":"791","article-title":"Screening of fetal chromosome aneuploidies in the first and second trimester of 125,170 Iranian pregnant women","volume":"44","author":"Seyyed-Kavoosi","year":"2015","journal-title":"Iranian Journal of Public Health."},{"issue":"1","key":"10.3233\/THC-213628_ref2","first-page":"38","article-title":"Prenatal diagnosis of fetal aneuploidies using QF-PCR in 333 cases","volume":"2","author":"Ahangari","year":"2016","journal-title":"Molecular Medicine Journal."},{"issue":"6","key":"10.3233\/THC-213628_ref4","first-page":"733","article-title":"Prevalence of congenital anomalies in Iran: A review article","volume":"46","author":"Vatankhah","year":"2017","journal-title":"Iranian Journal of Public Health."},{"key":"10.3233\/THC-213628_ref5","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1007\/978-90-481-9485-8_20","article-title":"The prevalence of congenital anomalies in Europe","volume":"686","author":"Dolk","year":"2010","journal-title":"Advances in Experimental Medicine and Biology."},{"issue":"2","key":"10.3233\/THC-213628_ref6","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1176\/jnp.2007.19.2.201","article-title":"Patau syndrome","volume":"19","author":"Nanjiani","year":"2007","journal-title":"J Neuropsychiatry Clin Neurosci."},{"issue":"3","key":"10.3233\/THC-213628_ref7","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1002\/ajmg.c.31511","article-title":"A tumor profile in Edwards syndrome (trisomy 18)","volume":"172","author":"Satg\u00e9","year":"2016","journal-title":"American Journal of Medical Genetics Part C: Seminars in Medical Genetics."},{"issue":"2","key":"10.3233\/THC-213628_ref8","first-page":"288","article-title":"Patau syndrome with a long survival. 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