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

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.