Artificial intelligence across oncology specialties: current applications and emerging tools

Frank Lin; Tim Rattay; John Kang; Evangelia Katsoulakis; Kyle Lafata; Ellen Kim; Christopher Yao; Harsha Nori; Christoph Ilsuk Lee

doi:10.1136/bmjonc-2023-000134

BMJ Oncology (Jul 2024)

Artificial intelligence across oncology specialties: current applications and emerging tools

Frank Lin,
Tim Rattay,
John Kang,
Evangelia Katsoulakis,
Kyle Lafata,
Ellen Kim,
Christopher Yao,
Harsha Nori,
Christoph Ilsuk Lee

Affiliations

Frank Lin: Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
Tim Rattay: Department of Genetics and Genome Biology, University of Leicester Cancer Research Centre, Leicester, UK
John Kang: Department of Radiation Oncology, University of Washington, Seattle, Washington, USA
Evangelia Katsoulakis: Department of Radiation Oncology, University of South Florida, Tampa, Florida, USA
Kyle Lafata: Department of Radiation Oncology, Duke University, Durham, North Carolina, USA
Ellen Kim: Department of Radiation Oncology, Brigham and Women`s Hospital, Boston, Massachusetts, USA
Christopher Yao: Department of Otolaryngology-Head & Neck Surgery, University of Toronto, Toronto, Ontario, Canada
Harsha Nori: Microsoft Research, Redmond, Washington, USA
Christoph Ilsuk Lee: Department of Radiology, University of Washington, Seattle, Washington, USA

DOI: https://doi.org/10.1136/bmjonc-2023-000134
Journal volume & issue: Vol. 3, no. 1

Abstract

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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.

Published in BMJ Oncology

ISSN: 2752-7948 (Online)
Publisher: BMJ Publishing Group
Country of publisher: United Kingdom
LCC subjects: Medicine: Internal medicine: Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Website: https://bmjoncology.bmj.com/

About the journal