{"title":"Pioneering new paths: the role of generative modelling in neurological disease research.","authors":"Moritz Seiler, Kerstin Ritter","doi":"10.1007/s00424-024-03016-w","DOIUrl":null,"url":null,"abstract":"<p><p>Recently, deep generative modelling has become an increasingly powerful tool with seminal work in a myriad of disciplines. This powerful modelling approach is supposed to not only have the potential to solve current problems in the medical field but also to enable personalised precision medicine and revolutionise healthcare through applications such as digital twins of patients. Here, the core concepts of generative modelling and popular modelling approaches are first introduced to consider the potential based on methodological concepts for the generation of synthetic data and the ability to learn a representation of observed data. These potentials will be reviewed using current applications in neuroimaging for data synthesis and disease decomposition in Alzheimer's disease and multiple sclerosis. Finally, challenges for further research and applications will be discussed, including computational and data requirements, model evaluation, and potential privacy risks.</p>","PeriodicalId":19954,"journal":{"name":"Pflugers Archiv : European journal of physiology","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pflugers Archiv : European journal of physiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00424-024-03016-w","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHYSIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Recently, deep generative modelling has become an increasingly powerful tool with seminal work in a myriad of disciplines. This powerful modelling approach is supposed to not only have the potential to solve current problems in the medical field but also to enable personalised precision medicine and revolutionise healthcare through applications such as digital twins of patients. Here, the core concepts of generative modelling and popular modelling approaches are first introduced to consider the potential based on methodological concepts for the generation of synthetic data and the ability to learn a representation of observed data. These potentials will be reviewed using current applications in neuroimaging for data synthesis and disease decomposition in Alzheimer's disease and multiple sclerosis. Finally, challenges for further research and applications will be discussed, including computational and data requirements, model evaluation, and potential privacy risks.
期刊介绍：
Pflügers Archiv European Journal of Physiology publishes those results of original research that are seen as advancing the physiological sciences, especially those providing mechanistic insights into physiological functions at the molecular and cellular level, and clearly conveying a physiological message. Submissions are encouraged that deal with the evaluation of molecular and cellular mechanisms of disease, ideally resulting in translational research. Purely descriptive papers covering applied physiology or clinical papers will be excluded. Papers on methodological topics will be considered if they contribute to the development of novel tools for further investigation of (patho)physiological mechanisms.
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