{"title":"髓母细胞瘤亚组初探","authors":"Marc Remke, Vijay Ramaswamy","doi":"10.1016/j.ccell.2024.06.011","DOIUrl":null,"url":null,"abstract":"<p>Recent incorporation of the four primary medulloblastoma subgroups into the WHO Classification of Central Nervous System Tumors necessitates globally accessible methods to discern subgroups. In this issue of <em>Cancer Cell</em>, Wang et al. develop a rapid and reliable machine learning workflow for pre-operative subgroup determination using routine magnetic resonance imaging.</p>","PeriodicalId":9670,"journal":{"name":"Cancer Cell","volume":null,"pages":null},"PeriodicalIF":48.8000,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Medulloblastoma subgrouping at first sight\",\"authors\":\"Marc Remke, Vijay Ramaswamy\",\"doi\":\"10.1016/j.ccell.2024.06.011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Recent incorporation of the four primary medulloblastoma subgroups into the WHO Classification of Central Nervous System Tumors necessitates globally accessible methods to discern subgroups. In this issue of <em>Cancer Cell</em>, Wang et al. develop a rapid and reliable machine learning workflow for pre-operative subgroup determination using routine magnetic resonance imaging.</p>\",\"PeriodicalId\":9670,\"journal\":{\"name\":\"Cancer Cell\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":48.8000,\"publicationDate\":\"2024-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Cell\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.ccell.2024.06.011\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Cell","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.ccell.2024.06.011","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
Recent incorporation of the four primary medulloblastoma subgroups into the WHO Classification of Central Nervous System Tumors necessitates globally accessible methods to discern subgroups. In this issue of Cancer Cell, Wang et al. develop a rapid and reliable machine learning workflow for pre-operative subgroup determination using routine magnetic resonance imaging.
期刊介绍：
Cancer Cell is a journal that focuses on promoting major advances in cancer research and oncology. The primary criteria for considering manuscripts are as follows:
Major advances: Manuscripts should provide significant advancements in answering important questions related to naturally occurring cancers.
Translational research: The journal welcomes translational research, which involves the application of basic scientific findings to human health and clinical practice.
Clinical investigations: Cancer Cell is interested in publishing clinical investigations that contribute to establishing new paradigms in the treatment, diagnosis, or prevention of cancers.
Insights into cancer biology: The journal values clinical investigations that provide important insights into cancer biology beyond what has been revealed by preclinical studies.
Mechanism-based proof-of-principle studies: Cancer Cell encourages the publication of mechanism-based proof-of-principle clinical studies, which demonstrate the feasibility of a specific therapeutic approach or diagnostic test.
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