L E Wadkin, I Makarenko, N G Parker, A Shukurov, F C Figueiredo, M Lako
{"title":"人类干细胞用于眼科：诊断图像分析和计算建模的最新进展》。","authors":"L E Wadkin, I Makarenko, N G Parker, A Shukurov, F C Figueiredo, M Lako","doi":"10.1007/s40778-023-00229-0","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose of review: </strong>To explore the advances and future research directions in image analysis and computational modelling of human stem cells (hSCs) for ophthalmological applications.</p><p><strong>Recent findings: </strong>hSCs hold great potential in ocular regenerative medicine due to their application in cell-based therapies and in disease modelling and drug discovery using state-of-the-art 2D and 3D organoid models. However, a deeper characterisation of their complex, multi-scale properties is required to optimise their translation to clinical practice. Image analysis combined with computational modelling is a powerful tool to explore mechanisms of hSC behaviour and aid clinical diagnosis and therapy.</p><p><strong>Summary: </strong>Many computational models draw on a variety of techniques, often blending continuum and discrete approaches, and have been used to describe cell differentiation and self-organisation. Machine learning tools are having a significant impact in model development and improving image classification processes for clinical diagnosis and treatment and will be the focus of much future research.</p>","PeriodicalId":37444,"journal":{"name":"Current Stem Cell Reports","volume":"9 4","pages":"57-66"},"PeriodicalIF":2.3000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10739444/pdf/","citationCount":"0","resultStr":"{\"title\":\"Human Stem Cells for Ophthalmology: Recent Advances in Diagnostic Image Analysis and Computational Modelling.\",\"authors\":\"L E Wadkin, I Makarenko, N G Parker, A Shukurov, F C Figueiredo, M Lako\",\"doi\":\"10.1007/s40778-023-00229-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose of review: </strong>To explore the advances and future research directions in image analysis and computational modelling of human stem cells (hSCs) for ophthalmological applications.</p><p><strong>Recent findings: </strong>hSCs hold great potential in ocular regenerative medicine due to their application in cell-based therapies and in disease modelling and drug discovery using state-of-the-art 2D and 3D organoid models. However, a deeper characterisation of their complex, multi-scale properties is required to optimise their translation to clinical practice. Image analysis combined with computational modelling is a powerful tool to explore mechanisms of hSC behaviour and aid clinical diagnosis and therapy.</p><p><strong>Summary: </strong>Many computational models draw on a variety of techniques, often blending continuum and discrete approaches, and have been used to describe cell differentiation and self-organisation. Machine learning tools are having a significant impact in model development and improving image classification processes for clinical diagnosis and treatment and will be the focus of much future research.</p>\",\"PeriodicalId\":37444,\"journal\":{\"name\":\"Current Stem Cell Reports\",\"volume\":\"9 4\",\"pages\":\"57-66\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10739444/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Stem Cell Reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s40778-023-00229-0\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/11/18 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"CELL & TISSUE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Stem Cell Reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40778-023-00229-0","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/11/18 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"CELL & TISSUE ENGINEERING","Score":null,"Total":0}
Human Stem Cells for Ophthalmology: Recent Advances in Diagnostic Image Analysis and Computational Modelling.
Purpose of review: To explore the advances and future research directions in image analysis and computational modelling of human stem cells (hSCs) for ophthalmological applications.
Recent findings: hSCs hold great potential in ocular regenerative medicine due to their application in cell-based therapies and in disease modelling and drug discovery using state-of-the-art 2D and 3D organoid models. However, a deeper characterisation of their complex, multi-scale properties is required to optimise their translation to clinical practice. Image analysis combined with computational modelling is a powerful tool to explore mechanisms of hSC behaviour and aid clinical diagnosis and therapy.
Summary: Many computational models draw on a variety of techniques, often blending continuum and discrete approaches, and have been used to describe cell differentiation and self-organisation. Machine learning tools are having a significant impact in model development and improving image classification processes for clinical diagnosis and treatment and will be the focus of much future research.
期刊介绍：
The goal of this journal is to publish cutting-edge reviews on subjects pertinent to all aspects of stem cell research, therapy, ethics, commercialization, and policy. We aim to provide incisive, insightful, and balanced contributions from leading experts in each relevant domain that will be of immediate interest to a wide readership of clinicians, basic scientists, and translational investigators.
We accomplish this aim by appointing major authorities to serve as Section Editors in key subject areas across the discipline. Section Editors select topics to be reviewed by leading experts who emphasize recent developments and highlight important papers published over the past year on their topics, in a crisp and readable format. We also provide commentaries from well-known figures in the field, and an Editorial Board of internationally diverse members suggests topics of special interest to their country/region and ensures that topics are current and include emerging research.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
