{"title":"The Use of Artificial Intelligence Technologies in Cancer Care.","authors":"P J Hoskin","doi":"10.1016/j.clon.2024.09.003","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) is already an essential tool in the handling of large data sets in epidemiology and basic research. Significant contributions to radiological diagnosis are emerging alongside increasing use of digital pathology. The future lies in integrating this information together with clinical data relevant to each individual patient. Linkage with clinical protocols will enable personalized management options to be presented to the oncologist of the future. Radiotherapy has the distinction of being the first to have a National Institute for Health and Care Excellence (NICE)-approved AI-based recommendation. There is the opportunity to revolutionize the workflow with many tasks currently undertaken by clinicians taken over by AI-based systems for volume outlining, planning, and quality assurance. Education and training will be essential to understand the AI processes and inputs. Clinicians will however have to feel confident interrogating the AI-derived information and in communicating AI-derived treatment plans to patients.</p>","PeriodicalId":10403,"journal":{"name":"Clinical oncology","volume":" ","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.clon.2024.09.003","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) is already an essential tool in the handling of large data sets in epidemiology and basic research. Significant contributions to radiological diagnosis are emerging alongside increasing use of digital pathology. The future lies in integrating this information together with clinical data relevant to each individual patient. Linkage with clinical protocols will enable personalized management options to be presented to the oncologist of the future. Radiotherapy has the distinction of being the first to have a National Institute for Health and Care Excellence (NICE)-approved AI-based recommendation. There is the opportunity to revolutionize the workflow with many tasks currently undertaken by clinicians taken over by AI-based systems for volume outlining, planning, and quality assurance. Education and training will be essential to understand the AI processes and inputs. Clinicians will however have to feel confident interrogating the AI-derived information and in communicating AI-derived treatment plans to patients.
期刊介绍：
Clinical Oncology is an International cancer journal covering all aspects of the clinical management of cancer patients, reflecting a multidisciplinary approach to therapy. Papers, editorials and reviews are published on all types of malignant disease embracing, pathology, diagnosis and treatment, including radiotherapy, chemotherapy, surgery, combined modality treatment and palliative care. Research and review papers covering epidemiology, radiobiology, radiation physics, tumour biology, and immunology are also published, together with letters to the editor, case reports and book reviews.
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