Tanja B Vojinovic, Zorica Potpara, M. Vukmirović, Nemanja Turkovic, S. Ibrić
{"title":"人工神经网络及其在卡马西平固体分散体优化中的应用","authors":"Tanja B Vojinovic, Zorica Potpara, M. Vukmirović, Nemanja Turkovic, S. Ibrić","doi":"10.32383/appdr/154044","DOIUrl":null,"url":null,"abstract":"The aim of this study was to examine the possibility of using artificial neural networks in the optimization of solid dispersions with carbamazepine. Artificial neural networks of the Generalized regression neural network type with four layers, gave models that describe the effect of components in solid dispersions carbamazepine-Neusilin ® UFL2 (magnesium aluminosilicate)-Collidon ® VA64 (vinylpyrrolidone-vinyl acetate) and dissolved carbamazepine value (%) after 10 (Q10) and 30(Q30) minutes of carbamazepine testing. After the learning process, root mean square error (RMS) values of 0.0029 were obtained for the training data set, and 0.1185 for the test training data, which is an excellent prediction of the neural network.","PeriodicalId":7147,"journal":{"name":"Acta poloniae pharmaceutica","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial neural networks and their application in the optimization of carbamazepine solid dispersions\",\"authors\":\"Tanja B Vojinovic, Zorica Potpara, M. Vukmirović, Nemanja Turkovic, S. Ibrić\",\"doi\":\"10.32383/appdr/154044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this study was to examine the possibility of using artificial neural networks in the optimization of solid dispersions with carbamazepine. Artificial neural networks of the Generalized regression neural network type with four layers, gave models that describe the effect of components in solid dispersions carbamazepine-Neusilin ® UFL2 (magnesium aluminosilicate)-Collidon ® VA64 (vinylpyrrolidone-vinyl acetate) and dissolved carbamazepine value (%) after 10 (Q10) and 30(Q30) minutes of carbamazepine testing. After the learning process, root mean square error (RMS) values of 0.0029 were obtained for the training data set, and 0.1185 for the test training data, which is an excellent prediction of the neural network.\",\"PeriodicalId\":7147,\"journal\":{\"name\":\"Acta poloniae pharmaceutica\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2022-11-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta poloniae pharmaceutica\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.32383/appdr/154044\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta poloniae pharmaceutica","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.32383/appdr/154044","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
Artificial neural networks and their application in the optimization of carbamazepine solid dispersions
The aim of this study was to examine the possibility of using artificial neural networks in the optimization of solid dispersions with carbamazepine. Artificial neural networks of the Generalized regression neural network type with four layers, gave models that describe the effect of components in solid dispersions carbamazepine-Neusilin ® UFL2 (magnesium aluminosilicate)-Collidon ® VA64 (vinylpyrrolidone-vinyl acetate) and dissolved carbamazepine value (%) after 10 (Q10) and 30(Q30) minutes of carbamazepine testing. After the learning process, root mean square error (RMS) values of 0.0029 were obtained for the training data set, and 0.1185 for the test training data, which is an excellent prediction of the neural network.
期刊介绍：
The international journal of the Polish Pharmaceutical Society is published in 6 issues a year. The journal offers Open Access publication of original research papers, short communications and reviews written in English, in all areas of pharmaceutical sciences. The following areas of pharmaceutical sciences are covered: Analysis, Biopharmacy, Drug Biochemistry, Drug Synthesis, Natural Drugs, Pharmaceutical Technology, Pharmacology and General.
A bimonthly appearing in English since 1994, which continues “Acta Poloniae Pharmaceutica”, whose first issue appeared in December 1937. The war halted the activity of the journal’s creators. Issuance of “Acta Poloniae Pharmaceutica” was resumed in 1947. From 1947 the journal appeared irregularly, initially as a quarterly, then a bimonthly. In the years 1963 – 1973 alongside the Polish version appeared the English edition of the journal. Starting from 1974 only works in English are published in the journal. Since 1995 the journal has been appearing very regularly in two-month intervals (six books a year). The journal publishes original works from all fields of pharmacy, summaries of postdoctoral dissertations and laboratory notes.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
