ReviewCancer discovery2024
Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions.
Review in Cancer discovery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 105 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
105 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Artificial intelligence-enabled liquid biopsy in cancer: a systematic review and meta- analysis of diagnostic performance and biological implications.Frontiers in oncology · 2026Pooled it
- "It's Not Only Attention We Need": Systematic Review of Large Language Models in Mental Health Care.JMIR mental health · 2025Pooled it
- Artificial intelligence networks for assessing the prognosis of gastrointestinal cancer to immunotherapy based on genetic mutation features: a systematic review and meta-analysis.BMC gastroenterology · 2025Pooled it
- Artificial Intelligence Performance in Image-Based Cancer Identification: Umbrella Review of Systematic Reviews.Journal of medical Internet research · 2025Pooled it
- Global research trends in the application of artificial intelligence in oncology care: a bibliometric study.Frontiers in oncology · 2024Pooled it
- Application of artificial intelligence in head and neck squamous cell carcinoma.Annals of medicine · 2026Review
- Radiomics beyond the visible-Decoding tumor heterogeneity to guide combination therapy of intermediate-stage HCC.Hepatology (Baltimore, Md.) · 2026Article
- Utilizing Machine Learning to Identify Multimodal Signatures for Patients Who Would Benefit from the Addition of Tremelimumab to Durvalumab and Chemotherapy (TRIDENT).Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Observational
- AI In Leukemia Diagnostics: Complementing the Pathologist's Role.International journal of laboratory hematology · 2026Review
- AI Perceptions, Professional Identity, and AI-Supported Clinical Decisions Among Medical Students and Clinicians: Cross-Sectional Survey and Quasi-Randomized Vignette Study.JMIR medical education · 2026Article
- AI Agents for Multimodal Oncology Diagnosis: Toward Transparent and Traceable Clinical Decision Support.JMIR cancer · 2026Review
- The use of generative AI tools among individuals with cancer and their caregivers: a cross-sectional study of awareness, attitudes, and experiences.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Article
- Review
- Chinese expert concern and consensus on applications of artificial intelligence in clinical cancer imaging.Insights into imaging · 2026Article
- A Narrative Review of Artificial Intelligence for Drug Repurposing: Lessons From COVID-19 and Oncology (2020-2025).CPT: pharmacometrics & systems pharmacology · 2026Review
- Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.International urology and nephrology · 2026Review
- A multi-modal approach for decision making in bladder cancer.Nature reviews. Urology · 2026Review
- Review
- Therapeutic repurposing of old drugs to modulate the tumor immune microenvironment and enhance immunotherapy efficacy.Journal of pharmaceutical analysis · 2026Review
- Development and validation of a dual-attention deep learning prediction model for noninvasive differentiation of pulmonary invasive mucinous adenocarcinoma from inflammatory pulmonary nodules.Translational lung cancer research · 2026Article
45 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
Abstract
Artificial intelligence (AI) in oncology is advancing beyond algorithm development to integration into clinical practice. This review describes the current state of the field, with a specific focus on clinical integration. AI applications are structured according to cancer type and clinical domain, focusing on the four most common cancers and tasks of detection, diagnosis, and treatment. These applications encompass various data modalities, including imaging, genomics, and medical records. We conclude with a summary of existing challenges, evolving solutions, and potential future directions for the field. SIGNIFICANCE: AI is increasingly being applied to all aspects of oncology, where several applications are maturing beyond research and development to direct clinical integration. This review summarizes the current state of the field through the lens of clinical translation along the clinical care continuum. Emerging areas are also highlighted, along with common challenges, evolving solutions, and potential future directions for the field.
Indexed as
Identifiers
What OpenQuestion holds
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.