Evidence map›Paper›PMID 39886165›Full record

ReviewBMJ oncology2024

Artificial intelligence across oncology specialties: current applications and emerging tools.

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

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in BMJ oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. AI and human expertise in cancer care - striving for synergy.Nature reviews. Clinical oncology · 2026
    Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

John KangDepartment of Radiation Oncology, University of Washington, Seattle, Washington, USA.ORCID 0000-0003-3915-8350
Kyle LafataDepartment of Radiation Oncology, Duke University, Durham, North Carolina, USA.
Ellen KimDepartment of Radiation Oncology, Brigham and Women's Hospital, Boston, Massachusetts, USA.ORCID 0000-0001-9379-0192
Christopher YaoDepartment of Otolaryngology-Head & Neck Surgery, University of Toronto, Toronto, Ontario, Canada.
Frank LinKinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia.
Tim RattayDepartment of Genetics and Genome Biology, University of Leicester Cancer Research Centre, Leicester, UK.
Harsha NoriMicrosoft Research, Redmond, Washington, USA.
Evangelia KatsoulakisDepartment of Radiation Oncology, University of South Florida, Tampa, Florida, USA.
Christoph Ilsuk LeeDepartment of Radiology, University of Washington, Seattle, Washington, USA.

Funding

Artificial Intelligence for Improved Breast Cancer Screening Accuracy: External Validation, Refinement, and Clinical TranslationR37CA240403 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI CHRISTOPH I LEE · 2020 to 2026
$3.8M
Population-Based Evaluation of Artificial Intelligence for Mammography Priorto Widespread Clinical TranslationR01CA262023 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI CHRISTOPH I LEE · 2022 to 2026
$3.2M
NCI NIH HHS R01 CA262023NCI NIH HHS R37 CA240403
6 · The paper itself

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.

Indexed as

BiomarkersClassificationMedical oncologyRadiation oncologySurgical oncology

Identifiers

PMID39886165
PMCPMC11203066

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.