Riccardo DE ROBERTIS, Flavio SPOTO, Francesca PASQUAZZO, Mirko D’ONOFRIO
{"title":"放射组学和人工智能的临床应用:预后分层和治疗反应","authors":"Riccardo DE ROBERTIS, Flavio SPOTO, Francesca PASQUAZZO, Mirko D’ONOFRIO","doi":"10.23736/s2723-9284.23.00245-9","DOIUrl":null,"url":null,"abstract":"The evaluation of treatment response and the noninvasive prognostic stratification of cancer patients are the most interesting and ambitious applications of radiomics and artificial intelligence, with potentially relevant clinical implications. Several studies reported promising results at this regard, even though their scientific quality is low and large-scale validation of the results is necessary. The purpose of this paper was to review systematic reviews and meta-analyses regarding the use of radiomics and artificial intelligence for prognostic stratification and evaluation of treatment response in cancer patients.","PeriodicalId":369070,"journal":{"name":"Journal of Radiological Review","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Clinical applications of radiomics and artificial intelligence: prognostic stratification and response to treatment\",\"authors\":\"Riccardo DE ROBERTIS, Flavio SPOTO, Francesca PASQUAZZO, Mirko D’ONOFRIO\",\"doi\":\"10.23736/s2723-9284.23.00245-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The evaluation of treatment response and the noninvasive prognostic stratification of cancer patients are the most interesting and ambitious applications of radiomics and artificial intelligence, with potentially relevant clinical implications. Several studies reported promising results at this regard, even though their scientific quality is low and large-scale validation of the results is necessary. The purpose of this paper was to review systematic reviews and meta-analyses regarding the use of radiomics and artificial intelligence for prognostic stratification and evaluation of treatment response in cancer patients.\",\"PeriodicalId\":369070,\"journal\":{\"name\":\"Journal of Radiological Review\",\"volume\":\"84 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Radiological Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23736/s2723-9284.23.00245-9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Radiological Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23736/s2723-9284.23.00245-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Clinical applications of radiomics and artificial intelligence: prognostic stratification and response to treatment
The evaluation of treatment response and the noninvasive prognostic stratification of cancer patients are the most interesting and ambitious applications of radiomics and artificial intelligence, with potentially relevant clinical implications. Several studies reported promising results at this regard, even though their scientific quality is low and large-scale validation of the results is necessary. The purpose of this paper was to review systematic reviews and meta-analyses regarding the use of radiomics and artificial intelligence for prognostic stratification and evaluation of treatment response in cancer patients.