ReviewCancer communications (London, England)2021
Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine.
Review in Cancer communications (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 115 papers, 5 of them syntheses that pooled 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.
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.
Who cites it
115 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Public Preferences for Emerging Cancer Screening Modalities: A Systematic Review of Discrete Choice Experiments.The patient · 2026Pooled it
- Current status and trends of machine learning applied in clinical research of gastric cancer from 2004 to 2023: global bibliometric and visual analysis.Frontiers in oncology · 2025Pooled it
- Accuracy of deep learning in diagnosis of apnea syndrome: a systematic review and meta-analysis.Frontiers in neurology · 2025Pooled it
- National and subnational incidence, mortality and associated factors of colorectal cancer in China: A systematic analysis and modelling study.Journal of global health · 2023Pooled it
- Identification of microbial markers associated with lung cancer based on multi-cohort 16 s rRNA analyses: A systematic review and meta-analysis.Cancer medicine · 2023Pooled it
- A Rehabilitation Model Conducive to Postoperative Recovery of Endometrial Cancer Patients after Laparoscopy.BioMed research international · 2022Trial
- Targeting lncRNA-regulated macrophage polarization: a novel therapeutic strategy for pancreatic ductal adenocarcinoma.Journal of physiology and biochemistry · 2026Review
- AI Adoption in US Cancer Centers: National Cross-Sectional Study of Institutional and Policy Determinants.Journal of medical Internet research · 2026Article
- Predictive performance precision analysis in medicine: identification of low-confidence predictions at patient and profile levels (MED3pa I).Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Fusion of Deep Transfer Learning and Radiomics in MRI-Based Prediction of Post-Surgical Recurrence in Soft Tissue Sarcoma.Journal of imaging informatics in medicine · 2026Article
- A new era of precision diagnosis and treatment for lung cancer: artificial intelligence-driven multimodal data integration and clinical applications.Cell death & disease · 2026Review
- [Advances in the Application of Artificial Intelligence in Clinical Microbiological Testing].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026Review
- Development and validation of machine learning-based risk prediction models of coronary artery disease using Porphyromonas gingivalis concentration.BMC oral health · 2026Article
- The impact of innovativeness on Chinese nurses' attitudes toward artificial intelligence: a cross-sectional study based on the technology acceptance model.BMC nursing · 2026Article
- Artificial intelligence for breast cancer management.Communications medicine · 2026Review
- Integrating Artificial Intelligence with Global Genomic Resources: A Narrative Review of Implications for Precision Medicine.Journal of multidisciplinary healthcare · 2026Review
- A radiomics-deep learning nomogram integrating intratumoral and peritumoral DCE-MRI features for pCR prediction in breast cancer.Frontiers in oncology · 2026Article
- Advancements in artificial intelligence for cancer diagnosis and prognosis prediction: current applications and emerging opportunities.Frontiers in cell and developmental biology · 2026Review
- Recent applications of artificial intelligence in cancer radiotherapy and immunotherapy: current status and future directions.Frontiers in immunology · 2026Review
- Utilizing artificial intelligence to optimize psychological trauma intervention in social assistances.Frontiers in psychology · 2026Article
55 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Over the past decade, artificial intelligence (AI) has contributed substantially to the resolution of various medical problems, including cancer. Deep learning (DL), a subfield of AI, is characterized by its ability to perform automated feature extraction and has great power in the assimilation and evaluation of large amounts of complicated data. On the basis of a large quantity of medical data and novel computational technologies, AI, especially DL, has been applied in various aspects of oncology research and has the potential to enhance cancer diagnosis and treatment. These applications range from early cancer detection, diagnosis, classification and grading, molecular characterization of tumors, prediction of patient outcomes and treatment responses, personalized treatment, automatic radiotherapy workflows, novel anti-cancer drug discovery, and clinical trials. In this review, we introduced the general principle of AI, summarized major areas of its application for cancer diagnosis and treatment, and discussed its future directions and remaining challenges. As the adoption of AI in clinical use is increasing, we anticipate the arrival of AI-powered cancer care.
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Registered trials
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 OpenQuestion graph.