Artificial intelligence across oncology specialties: Current applications and emerging tools

10Citations
Citations of this article
29Readers
Mendeley users who have this article in their library.

Abstract

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.

Cite

CITATION STYLE

APA

Kang, J., Lafata, K., Kim, E., Yao, C., Lin, F., Rattay, T., … Lee, C. I. (2024, January 17). Artificial intelligence across oncology specialties: Current applications and emerging tools. BMJ Oncology. BMJ Publishing Group. https://doi.org/10.1136/bmjonc-2023-000134

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free