基于iPSC心肌细胞钙瞬态信号的药物影响机器学习

2022 Computing in Cardiology (CinC) Pub Date : 2022-09-04 DOI:10.22489/CinC.2022.167

M. Juhola, H. Joutsijoki, R. Pölönen, K. Aalto-Setälä

{"title":"基于iPSC心肌细胞钙瞬态信号的药物影响机器学习","authors":"M. Juhola, H. Joutsijoki, R. Pölönen, K. Aalto-Setälä","doi":"10.22489/CinC.2022.167","DOIUrl":null,"url":null,"abstract":"Machine learning was applied to classify potential influence of two drugs on induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) on the basis of peak data detected from calcium transient signals of iPsC-CMs. The study shows that machine learning is capable to analyze such influence.","PeriodicalId":117840,"journal":{"name":"2022 Computing in Cardiology (CinC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Machine Learning of Drug Influence Based on iPSC Cardiomyocyte Calcium Transient Signals\",\"authors\":\"M. Juhola, H. Joutsijoki, R. Pölönen, K. Aalto-Setälä\",\"doi\":\"10.22489/CinC.2022.167\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Machine learning was applied to classify potential influence of two drugs on induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) on the basis of peak data detected from calcium transient signals of iPsC-CMs. The study shows that machine learning is capable to analyze such influence.\",\"PeriodicalId\":117840,\"journal\":{\"name\":\"2022 Computing in Cardiology (CinC)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Computing in Cardiology (CinC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22489/CinC.2022.167\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Computing in Cardiology (CinC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22489/CinC.2022.167","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

基于从诱导多能干细胞- cm的钙瞬态信号中检测到的峰值数据，应用机器学习对两种药物对诱导多能干细胞- cm的潜在影响进行分类。该研究表明，机器学习能够分析这种影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Machine Learning of Drug Influence Based on iPSC Cardiomyocyte Calcium Transient Signals

Machine learning was applied to classify potential influence of two drugs on induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) on the basis of peak data detected from calcium transient signals of iPsC-CMs. The study shows that machine learning is capable to analyze such influence.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2022 Computing in Cardiology (CinC)

自引率

0.00%

发文量