Thomas Alassane Ouattara, Seydou Golo Barro, Pascal Staccini
{"title":"Development of an AI Platform for Advanced Breast Cancer Management.","authors":"Thomas Alassane Ouattara, Seydou Golo Barro, Pascal Staccini","doi":"10.3233/SHTI241095","DOIUrl":null,"url":null,"abstract":"<p><p>This article explores the transition from a traditional histopathological examination system to an innovative platform using artificial intelligence (AI) for breast cancer detection from histopathological images in Burkina Faso. The existing system is analyzed in detail, highlighting the steps of querying, sample preparation, analysis by the pathologist, and validation by the physician. From this analysis, the needs and challenges are identified, emphasizing the opportunities for AI to improve the efficiency and accuracy of the diagnosis. The design of the AI platform is then presented, including data collection, AI model development, and its integration into existing processes. Finally, the expected results and implications for improving healthcare in Burkina Faso are discussed, highlighting the potential benefits and challenges to overcome for the successful adoption of this promising technology.</p>","PeriodicalId":94357,"journal":{"name":"Studies in health technology and informatics","volume":"321 ","pages":"215-219"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Studies in health technology and informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/SHTI241095","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
This article explores the transition from a traditional histopathological examination system to an innovative platform using artificial intelligence (AI) for breast cancer detection from histopathological images in Burkina Faso. The existing system is analyzed in detail, highlighting the steps of querying, sample preparation, analysis by the pathologist, and validation by the physician. From this analysis, the needs and challenges are identified, emphasizing the opportunities for AI to improve the efficiency and accuracy of the diagnosis. The design of the AI platform is then presented, including data collection, AI model development, and its integration into existing processes. Finally, the expected results and implications for improving healthcare in Burkina Faso are discussed, highlighting the potential benefits and challenges to overcome for the successful adoption of this promising technology.
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