{"title":"Artificial Intelligence in Oncology: The Wins, The Challenges, and How We Can Deliver on Personalized Cancer Care","authors":"Matthew Biancalana, Tushar Pandey","doi":"10.25270/jcp.2023.09.03","DOIUrl":null,"url":null,"abstract":"The development of effective, targeted therapies for cancer remains one of the primary goals in precision medicine, requiring the input of multiple disciplines across the diagnostic and therapeutic landscape. Despite the significant role of cancer care in medicine, there is a forecasted shortfall of physicians able to diagnose and treat patients along their cancer diagnosis journey, which is only projected to worsen in the coming decades. Artificial intelligence (AI), and its manifestations in both machine learning and deep learning, are poised to unburden physicians from many laborious and repetitive tasks in diagnostic analyses, while also providing insight into prospective therapeutic options. AI will increasingly facilitate decision-making as well as improve the accuracy and relevance of therapeutic recommendations. This collaborative interaction between algorithms and physicians promises to enhance the field of precision medicine and further enable optimal patient care.","PeriodicalId":73670,"journal":{"name":"Journal of clinical pathways : the foundation of value-based care","volume":"47 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 clinical pathways : the foundation of value-based care","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25270/jcp.2023.09.03","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
The development of effective, targeted therapies for cancer remains one of the primary goals in precision medicine, requiring the input of multiple disciplines across the diagnostic and therapeutic landscape. Despite the significant role of cancer care in medicine, there is a forecasted shortfall of physicians able to diagnose and treat patients along their cancer diagnosis journey, which is only projected to worsen in the coming decades. Artificial intelligence (AI), and its manifestations in both machine learning and deep learning, are poised to unburden physicians from many laborious and repetitive tasks in diagnostic analyses, while also providing insight into prospective therapeutic options. AI will increasingly facilitate decision-making as well as improve the accuracy and relevance of therapeutic recommendations. This collaborative interaction between algorithms and physicians promises to enhance the field of precision medicine and further enable optimal patient care.