{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T02:39:05Z","timestamp":1747190345767,"version":"3.40.5"},"reference-count":17,"publisher":"Wiley","license":[{"start":{"date-parts":[[2020,3,11]],"date-time":"2020-03-11T00:00:00Z","timestamp":1583884800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2020,3,11]]},"abstract":"<jats:p>With the continuous advancement of medical technology, the survival rate of high-risk children is increasing year by year, but the developmental problems that have gradually become apparent in the later stages have a serious impact on the quality of life of children. Amplitude-integrated EEG is an EEG monitoring technology developed for clinical use in newborns in recent years. Therefore, to better detect neuromata development in high-risk children, this study explores the validity prediction of amplitude-integrated EEG in early neuromata development in high-risk children. For 100 high-risk children, amplitude-integrated EEG was used for monitoring, and the exercise scale and validity predictors in the Bailey Infant Development Scale were used to assess whether high-risk children had neurobehavioral abnormalities. The experimental results show that the application of amplitude-integrated EEG can make accurate and effective predictions of early neuromata development outcomes in high-risk children. Compared with traditional neurological examination methods, it has higher sensitivity, specificity, positive predictive value, and consistency in predicting the early neuromata development outcomes of high-risk children. It is suitable for application and promotion in China and has a good application value.<\/jats:p>","DOI":"10.1155\/2020\/9438248","type":"journal-article","created":{"date-parts":[[2020,3,11]],"date-time":"2020-03-11T19:31:55Z","timestamp":1583955115000},"page":"1-8","source":"Crossref","is-referenced-by-count":1,"title":["Validity Prediction of Amplitude-Integrated EEG in Early Neuromotor Development Outcomes in High-Risk Neonates"],"prefix":"10.1155","volume":"2020","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0348-3637","authenticated-orcid":true,"given":"Jian","family":"Guo","sequence":"first","affiliation":[{"name":"Affiliated Hospital of Chengde Medical College, Chengde, Hebei 067000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8909-6085","authenticated-orcid":true,"given":"Wentao","family":"Wang","sequence":"additional","affiliation":[{"name":"Affiliated Hospital of Chengde Medical College, Chengde, Hebei 067000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2957-3000","authenticated-orcid":true,"given":"Qili","family":"Zhou","sequence":"additional","affiliation":[{"name":"Affiliated Hospital of Chengde Medical College, Chengde, Hebei 067000, China"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1007\/s10803-017-3447-z"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ridd.2017.10.011"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1016\/j.jaac.2018.06.024"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1016\/j.brainresbull.2018.05.005"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinph.2019.05.001"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1016\/j.siny.2018.02.003"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1177\/0883073818778468"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1111\/dmcn.13697"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1016\/j.clp.2018.05.011"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymgme.2018.08.011"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinph.2018.01.019"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1097\/anc.0000000000000523"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1080\/14767058.2017.1304536"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1111\/apa.14460"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1007\/s00431-018-3166-2"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1144\/sp482.11"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1007\/s00431-019-03364-1"}],"container-title":["Computational and Mathematical Methods in Medicine"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2020\/9438248.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2020\/9438248.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2020\/9438248.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,3,11]],"date-time":"2020-03-11T19:31:56Z","timestamp":1583955116000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/cmmm\/2020\/9438248\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,11]]},"references-count":17,"alternative-id":["9438248","9438248"],"URL":"https:\/\/doi.org\/10.1155\/2020\/9438248","relation":{},"ISSN":["1748-670X","1748-6718"],"issn-type":[{"type":"print","value":"1748-670X"},{"type":"electronic","value":"1748-6718"}],"subject":[],"published":{"date-parts":[[2020,3,11]]}}}