Artificial intelligence across oncology specialties: current applications and emerging tools
Oncology is becoming increasingly personalised through advancements in precision in diagnostics and therapeutics, with more and more data available on both ends to create individualised plans. The depth and breadth of data are outpacing our natural ability to interpret it. Artificial intelligence (A...
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2024-07-01
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| Series: | BMJ Oncology |
| Online Access: | https://bmjoncology.bmj.com/content/3/1/e000134.full |
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| _version_ | 1832581898023469056 |
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| author | Frank Lin Tim Rattay John Kang Evangelia Katsoulakis Kyle Lafata Ellen Kim Christopher Yao Harsha Nori Christoph Ilsuk Lee |
| author_facet | Frank Lin Tim Rattay John Kang Evangelia Katsoulakis Kyle Lafata Ellen Kim Christopher Yao Harsha Nori Christoph Ilsuk Lee |
| author_sort | Frank Lin |
| collection | DOAJ |
| description | Oncology is becoming increasingly personalised through advancements in precision in diagnostics and therapeutics, with more and more data available on both ends to create individualised plans. The depth and breadth of data are outpacing our natural ability to interpret it. Artificial intelligence (AI) provides a solution to ingest and digest this data deluge to improve detection, prediction and skill development. In this review, we provide multidisciplinary perspectives on oncology applications touched by AI—imaging, pathology, patient triage, radiotherapy, genomics-driven therapy and surgery—and integration with existing tools—natural language processing, digital twins and clinical informatics. |
| format | Article |
| id | doaj-art-6317e7c27c1744d1a4da2e2e35cdc2d9 |
| institution | Kabale University |
| issn | 2752-7948 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Oncology |
| spelling | doaj-art-6317e7c27c1744d1a4da2e2e35cdc2d92025-01-30T09:50:08ZengBMJ Publishing GroupBMJ Oncology2752-79482024-07-013110.1136/bmjonc-2023-000134Artificial intelligence across oncology specialties: current applications and emerging toolsFrank Lin0Tim Rattay1John Kang2Evangelia Katsoulakis3Kyle Lafata4Ellen Kim5Christopher Yao6Harsha Nori7Christoph Ilsuk Lee8Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, New South Wales, AustraliaDepartment of Genetics and Genome Biology, University of Leicester Cancer Research Centre, Leicester, UKDepartment of Radiation Oncology, University of Washington, Seattle, Washington, USADepartment of Radiation Oncology, University of South Florida, Tampa, Florida, USADepartment of Radiation Oncology, Duke University, Durham, North Carolina, USADepartment of Radiation Oncology, Brigham and Women`s Hospital, Boston, Massachusetts, USADepartment of Otolaryngology-Head & Neck Surgery, University of Toronto, Toronto, Ontario, CanadaMicrosoft Research, Redmond, Washington, USADepartment of Radiology, University of Washington, Seattle, Washington, USAOncology is becoming increasingly personalised through advancements in precision in diagnostics and therapeutics, with more and more data available on both ends to create individualised plans. The depth and breadth of data are outpacing our natural ability to interpret it. Artificial intelligence (AI) provides a solution to ingest and digest this data deluge to improve detection, prediction and skill development. In this review, we provide multidisciplinary perspectives on oncology applications touched by AI—imaging, pathology, patient triage, radiotherapy, genomics-driven therapy and surgery—and integration with existing tools—natural language processing, digital twins and clinical informatics.https://bmjoncology.bmj.com/content/3/1/e000134.full |
| spellingShingle | Frank Lin Tim Rattay John Kang Evangelia Katsoulakis Kyle Lafata Ellen Kim Christopher Yao Harsha Nori Christoph Ilsuk Lee Artificial intelligence across oncology specialties: current applications and emerging tools BMJ Oncology |
| title | Artificial intelligence across oncology specialties: current applications and emerging tools |
| title_full | Artificial intelligence across oncology specialties: current applications and emerging tools |
| title_fullStr | Artificial intelligence across oncology specialties: current applications and emerging tools |
| title_full_unstemmed | Artificial intelligence across oncology specialties: current applications and emerging tools |
| title_short | Artificial intelligence across oncology specialties: current applications and emerging tools |
| title_sort | artificial intelligence across oncology specialties current applications and emerging tools |
| url | https://bmjoncology.bmj.com/content/3/1/e000134.full |
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