ReviewNPJ precision oncology2026
The impact of AI on modern oncology from early detection to personalized cancer treatment.
Review in NPJ precision oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed.
- [Artificial intelligence in the care of geriatric patients-more of a curse or more of a blessing?]Urologie (Heidelberg, Germany) · 2026Review
- Decoding and Overcoming Temozolomide Resistance Through CRISPR/Cas Technologies.Molecular diagnosis & therapy · 2026Review
- A Scoping Review of Implemented Innovations in Cancer Care: Implications for Pan-Canadian Scaling.Current oncology (Toronto, Ont.) · 2026Article
- Artificial Intelligence-Assisted Quantification of Longitudinal HRCT Changes During Treatment of Pulmonary Tuberculosis: An Exploratory Proof-of-Concept Study.Diagnostics (Basel, Switzerland) · 2026Article
- Precision Medicine in Non-Hodgkin Lymphoma: Advances in BTK Inhibition, CD30-Directed Antibody-Drug Conjugates, and HDAC-Mediated Epigenetic Therapy with Pirtobrutinib, Brentuximab Vedotin, and Belinostat.Journal of clinical medicine · 2026Review
- Two Worlds, One Battle: How Bacteria and Malignancies Converge on Drug Resistance.International journal of molecular sciences · 2026Review
- Liquid Biopsy in Colorectal Cancer: Future Perspectives Through the Lens of Artificial Intelligence-A Comprehensive Review of Novel Literature.International journal of molecular sciences · 2026Review
- Genomic innovations in cancer prevention, diagnosis, prognosis and precision therapeutics.Frontiers in genetics · 2026Review
- Editorial: AI-powered integrative multi-omics for precision cancer therapies.Frontiers in cell and developmental biology · 2026Article
- A novel explainable AI for revealing determinants of cancer drug response through integrative multi-omics analysis.Frontiers in oncology · 2026Article
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
Artificial intelligence (AI) is quickly becoming a revolutionary and game-changing tool in modern oncology, with promising uses in early diagnosis and drug discovery. Machine learning (ML), deep learning (DL), reinforcement learning (RL), natural language processing (NLP), and generative models are some of the AI methods that are becoming very important for cancer care. With an emphasis on early diagnosis, mutation mapping, and drug design, this article aims to review the existing literature and investigate the role of AI technologies in oncology.
Identifiers
What Socratic 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 Socratic graph.