{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T13:21:13Z","timestamp":1777728073725,"version":"3.51.4"},"reference-count":44,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2019,4,30]],"date-time":"2019-04-30T00:00:00Z","timestamp":1556582400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31271097"],"award-info":[{"award-number":["31271097"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Int Med Res"],"published-print":{"date-parts":[[2020,1]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Atherosclerosis (AS) is the main pathological basis of ischemic cardio-cerebrovascular diseases, and the intimal thickness (IT) of large arteries is regarded as a powerful evaluation indicator for AS. We established an effective neural network model for automatic prediction of the IT and analyzed the high-risk warning indicators of IT.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The weight of the left adrenal (WLA) was evaluated. The serum interleukin-6 (IL-6) concentration was measured by enzyme-linked immunosorbent assay. The statistical methods included neural network modeling, a cubic spline interpolation algorithm, Spearman\u2019s rho test, and linear fit.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Thirty-seven rabbits were classified into a control group (n\u2009=\u200911), high-fat diet group (n\u2009=\u200913), and high-fat diet plus chronic stress group (n\u2009=\u200913). The neural network model was successfully established and verified by comparing the predicted IT with the actual IT. The high-risk warning indicator of IT was identified as follows: 0.445\u2009g\u2009&lt;\u2009WLA\u2009&lt;\u20090.610\u2009g and 60\u2009ng\/L&lt;\u2009IL-6\u2009&lt;\u200980 ng\/L.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The neural network model based on WLA and IL-6 could predict the IT of AS. When 0.445\u2009g\u2009&lt;\u2009WLA\u2009&lt;\u20090.610\u2009g and 60\u2009ng\/L\u2009&lt;\u2009IL-6\u2009&lt;\u200980\u2009ng\/L, the risk to developing AS is very high.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/0300060519839625","type":"journal-article","created":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T02:34:27Z","timestamp":1556678067000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Computer-assisted prediction of atherosclerotic intimal thickness based on weight of adrenal gland, interleukin-6 concentration, and neural networks"],"prefix":"10.1177","volume":"48","author":[{"given":"Ling-bing","family":"Meng","sequence":"first","affiliation":[{"name":"Neurology Department, Beijing Hospital, National Center of Gerontology, Beijing, P.R. 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