ReviewFrontiers in oncology2022
Artificial intelligence assists precision medicine in cancer treatment.
Review in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers, 4 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
95 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Immune Checkpoint Inhibitors: efficacy, safety, and biomarkers - a systematic review.Frontiers in oncology · 2026Pooled it
- Artificial intelligence in vaccine research and development: an umbrella review.Frontiers in immunology · 2025Pooled it
- Advancements in Image-Based Analyses for Morphology and Staging of Colon Cancer: A Comprehensive Review.BioMed research international · 2025Pooled it
- Bibliometric and visual analysis of radiomics for evaluating lymph node status in oncology.Frontiers in medicine · 2024Pooled it
- Artificial Intelligence in Clinical Genetics: Current Applications and Challenges.Indian journal of pediatrics · 2026Review
- Global Curriculum in Surgical Oncology: 2nd Edition, 2026.Annals of surgical oncology · 2026Review
- Applications of Artificial Intelligence in Cancer Diagnosis and Treatment.Cancer medicine · 2026Review
- The Oncology Research Information Exchange Network (ORIEN) - Building a Real-World Collaborative, Patient-driven Infrastructure for Discovery Research and Precision Oncology.Research square · 2026Article
- Artificial intelligence in cancer diagnosis and therapy using sex and gender as precision biomarkers.Discover oncology · 2026Review
- Nanotechnology in Cancer Therapy: How Nanoparticles Are Shaping the Future of Personalized Treatment.ACS nano medicine · 2026Review
- Leveraging population-scale proteomic data with deep learning for head and neck cancer detection in saliva.NPJ digital medicine · 2026Article
- Next-Generation Artificial Intelligence Strategies for Mechanistic Cancer Target Discovery and Drug Development: A State-of-the-Art Review.International journal of molecular sciences · 2026Review
- Chemoresistance in gynecologic cancers: mechanistic insights and emerging platforms to overcome drug failure.Journal of ovarian research · 2026Review
- Accuracy and usability of artificial intelligence chatbot generated chemotherapy protocols.Future oncology (London, England) · 2026Article
- Decades of omics in lung cancer research: a bibliometric analysis and visualization from 2004 to 2024.Journal of thoracic disease · 2026Article
- Public perceptions of AI-assisted cancer care in Abu Dhabi, UAE: A cross-sectional survey.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Article
- The impact of AI on modern oncology from early detection to personalized cancer treatment.NPJ precision oncology · 2026Review
- Leveraging AI for cell biology discovery.Biochemical Society transactions · 2026Review
- Artificial intelligence and machine learning-driven advancements in gastrointestinal cancer: Paving the way for precision medicine.World journal of gastroenterology · 2026Review
- Ensemble transformer-based multiple instance learning for predicting neoadjuvant chemotherapy response from breast cancer biopsy whole-slide images.Frontiers in oncology · 2026Article
35 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer is a major medical problem worldwide. Due to its high heterogeneity, the use of the same drugs or surgical methods in patients with the same tumor may have different curative effects, leading to the need for more accurate treatment methods for tumors and personalized treatments for patients. The precise treatment of tumors is essential, which renders obtaining an in-depth understanding of the changes that tumors undergo urgent, including changes in their genes, proteins and cancer cell phenotypes, in order to develop targeted treatment strategies for patients. Artificial intelligence (AI) based on big data can extract the hidden patterns, important information, and corresponding knowledge behind the enormous amount of data. For example, the ML and deep learning of subsets of AI can be used to mine the deep-level information in genomics, transcriptomics, proteomics, radiomics, digital pathological images, and other data, which can make clinicians synthetically and comprehensively understand tumors. In addition, AI can find new biomarkers from data to assist tumor screening, detection, diagnosis, treatment and prognosis prediction, so as to providing the best treatment for individual patients and improving their clinical outcomes.
Indexed as
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.