{"title":"Successful deployment of an Artificial Intelligence solution for primary diagnosis of prostate biopsies in clinical practice","authors":"Muhammad Aslam, Alistair Heath","doi":"10.47184/tp.2023.01.03","DOIUrl":null,"url":null,"abstract":"In order to evaluate the feasibility of artificial intelligence within the setting of prostate histopathology, 3975 slides from 860 patients were digitally scanned and supplied to the IBEX-Artificial Intelligence (AI) system before evaluation by histopathology consultants with recommendations from the AI. Data comparing reporting with and without AI assistance were analysed along with accuracy of diagnosis for the AI. Request rates for additional immunohistochemistry from consultants in cases of diagnostic uncertainty dropped from 8.7 % to 4.5 %. Qualitative reporting confidence increased with AI assistance and valued the highlighting of the most suspicious areas within a biopsy. Positive and negative predictive values for the AI were 0.994 and 0.995 when using the consultants’ diagnosis as the true value. AI shows significant potential as an assistant for histopathologists in the field of cancer diagnosis.","PeriodicalId":126763,"journal":{"name":"Trillium Pathology","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trillium Pathology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47184/tp.2023.01.03","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In order to evaluate the feasibility of artificial intelligence within the setting of prostate histopathology, 3975 slides from 860 patients were digitally scanned and supplied to the IBEX-Artificial Intelligence (AI) system before evaluation by histopathology consultants with recommendations from the AI. Data comparing reporting with and without AI assistance were analysed along with accuracy of diagnosis for the AI. Request rates for additional immunohistochemistry from consultants in cases of diagnostic uncertainty dropped from 8.7 % to 4.5 %. Qualitative reporting confidence increased with AI assistance and valued the highlighting of the most suspicious areas within a biopsy. Positive and negative predictive values for the AI were 0.994 and 0.995 when using the consultants’ diagnosis as the true value. AI shows significant potential as an assistant for histopathologists in the field of cancer diagnosis.