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Cited by 281AI in cancer detectionArtificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.

Artificial intelligence in oncology: current applications and future perspectives

Open access
Luchini, Claudio, Pea, Antonio, Scarpa, Aldo·2022·British Journal of Cancer
DOI 10.1038/s41416-021-01633-1PMC PMC8727615
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Abstract

Artificial intelligence (AI) is concretely reshaping the landscape and horizons of oncology, opening new important opportunities for improving the management of cancer patients. Analysing the AI-based devices that have already obtained the official approval by the Federal Drug Administration (FDA), here we show that cancer diagnostics is the oncology-related area in which AI is already entered with the largest impact into clinical practice. Furthermore, breast, lung and prostate cancers represent the specific cancer types that now are experiencing more advantages from AI-based devices. The future perspectives of AI in oncology are discussed: the creation of multidisciplinary platforms, the comprehension of the importance of all neoplasms, including rare tumours and the continuous support for guaranteeing its growth represent in this time the most important challenges for finalising the 'AI-revolution' in oncology.

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Fig. 1 Current status of Artificial intelligence in oncology and related fields. Summarising representations of the artificial intelligence-based devices, FDA-approved, expressed by oncology-related specialties (a: cancer radiology 54.9%, pathology 19.7%, radiation oncology 8.5%, gastroenterology 8.5%, clinical oncology 7.0% and gynaecology 1.4%) and by tumour types (b: general cancers 33.8%, breast cancer 31.0%, lung cancer 8.5%, prostate cancer 8.5%, colorectal cancer 7.0% and brain tumours 2.8%, others: 6 tumour types, 1.4% each).
Fig. 1 Current status of Artificial intelligence in oncology and related fields. Summarising representations of the artificial intelligence-based devices, FDA-approved, expressed by oncology-related specialties (a: cancer radiology 54.9%, pathology 19.7%, radiation oncology 8.5%, gastroenterology 8.5%, clinical oncology 7.0% and gynaecology 1.4%) and by tumour types (b: general cancers 33.8%, breast cancer 31.0%, lung cancer 8.5%, prostate cancer 8.5%, colorectal cancer 7.0% and brain tumours 2.8%, others: 6 tumour types, 1.4% each).CC BY · PubMed Central

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Metadata

Authors
Luchini, C., Pea, A., & Scarpa, A.
Affiliations
University of Verona (IT)
Corresponding author
  • Luchini, Claudio
  • Scarpa, Aldo
ORCID
Venue
British Journal of Cancer
Publisher
Springer Science and Business Media LLC
Published
2021-11-26
Volume
126
Issue
1
Pages
4-9
ISSN
  • 0007-0920 (ISSN-L)
  • 1532-1827
DOI
10.1038/s41416-021-01633-1
PMC
PMC8727615
OpenAlex
W3215393627
Cited by
281
References
14
Citations by year
2026: 56 · 2025: 83 · 2024: 71 · 2023: 43 · 2022: 28
FWCI
12.50
Type
journal article
Language
en
Open access
Licence
Locations
  • British Journal of Cancer (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • Associazione Italiana per la Ricerca sul Cancro (12182)
  • Fondazione Cassa di Risparmio di Verona Vicenza Belluno e Ancona (203885/2017)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
Keywords
artificial intelligence in oncology, AI-based medical devices, cancer diagnosis, breast cancer, lung cancer, prostate cancer, rare tumor, clinical implementation of AI
MeSH terms
Artificial Intelligence, Forecasting, Humans, Medical Oncology, Neoplasms

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