{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T14:44:25Z","timestamp":1753886665761,"version":"3.41.2"},"reference-count":13,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2011,7,24]],"date-time":"2011-07-24T00:00:00Z","timestamp":1311465600000},"content-version":"vor","delay-in-days":204,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["30772342"],"award-info":[{"award-number":["30772342"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["BioMed Research International"],"published-print":{"date-parts":[[2011,1]]},"abstract":"<jats:p><jats:italic>Objective<\/jats:italic>. To establish an early diagnostic system for hypoxic ischemic encephalopathy (HIE) in newborns based on artificial neural networks and to determine its feasibility. <jats:italic>Methods<\/jats:italic>. Based on published research as well as preliminary studies in our laboratory, multiple noninvasive indicators with high sensitivity and specificity were selected for the early diagnosis of HIE and employed in the present study, which incorporates fuzzy logic with artificial neural networks. <jats:italic>Results<\/jats:italic>. The analysis of the diagnostic results from the fuzzy neural network experiments with 140 cases of HIE showed a correct recognition rate of 100% in all training samples and a correct recognition rate of 95% in all the test samples, indicating a misdiagnosis rate of 5%. <jats:italic>Conclusion<\/jats:italic>. A preliminary model using fuzzy backpropagation neural networks based on a composite index of clinical indicators was established and its accuracy for the early diagnosis of HIE was validated. Therefore, this method provides a convenient tool for the early clinical diagnosis of HIE.<\/jats:p>","DOI":"10.1155\/2011\/349490","type":"journal-article","created":{"date-parts":[[2011,7,24]],"date-time":"2011-07-24T19:00:42Z","timestamp":1311534042000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["The Use of Fuzzy BackPropagation Neural Networks for the Early Diagnosis of Hypoxic Ischemic Encephalopathy in Newborns"],"prefix":"10.1155","volume":"2011","author":[{"given":"Liu","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huo","family":"Liqing","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lu","family":"Hongru","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhang","family":"Feng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zheng","family":"Chongxun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shami","family":"Pokhrel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhang","family":"Jie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2011,7,24]]},"reference":[{"volume-title":"The Principle and Application of Artificial Neural Network","year":"2006","author":"Zhu D. 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H. The applied of research neural networks in medical diagnosis. Full-text databaseof China\u2032s outstanding M.S. thesis 2007."},{"key":"e_1_2_10_11_2","first-page":"781","article-title":"Research of fuzzy control based on artificial neural network in medicine diagnostic system","volume":"23","author":"Xu D. J.","year":"2005","journal-title":"Chinese Archives of Traditional Chinese Medicine"},{"key":"e_1_2_10_12_2","first-page":"295","article-title":"The application of fuzzy neural network to lung cancer diagnosis","volume":"25","author":"Wan X. F.","year":"2009","journal-title":"Microcomputer Information"},{"volume-title":"Numerical Optimization of Computer Model","year":"1981","author":"Schwefel H. 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