ReviewFrontiers in oncology2023
Applications of large language models in cancer care: current evidence and future perspectives.
Review in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 3 of them syntheses that pooled it.
What it found
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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.
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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
54 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Deep representation learning for temporal inference in cancer omics: a systematic literature review.Briefings in bioinformatics · 2026Pooled it
- Performance of Natural Language Processing for Information Extraction From Electronic Health Records Within Cancer: Systematic Review.JMIR medical informatics · 2025Pooled it
- The application of ChatGPT in nursing: a bibliometric and visualized analysis.Frontiers in medicine · 2024Pooled it
- The Usability and Experience of Artificial Intelligence-Based Conversational Agents in Health Education for Cancer Patients: A Scoping Review.Journal of clinical nursing · 2026Article
- Alignment between AI clinical decision tools and multidisciplinary tumor board decisions in prostate cancer.International urology and nephrology · 2026Article
- Article
- Beyond classical models: LLM-driven survival analysis for breast cancer prognosis using European cancer registry data.BMC medical informatics and decision making · 2026Article
- Article
- Large Language Models in Patient Health Communication for Atherosclerotic Cardiovascular Disease: Pilot Cross-Sectional Comparative Analysis.JMIR medical informatics · 2026Article
- A generative AI multi-agent framework with integrated XAI governance for cancer diagnostics: from multi-omics interpretation to lifestyle risk stratification.Frontiers in systems biology · 2026Review
- Application of the artificial intelligence-assisted World Café teaching model in clinical pharmacology graduate course: a pilot study.Frontiers in public health · 2026Article
- Large Language Models for Cardiovascular Disease, Cancer, and Mental Disorders: A Review of Systematic Reviews.Healthcare (Basel, Switzerland) · 2025Review
- Large Language Models for Drug-Related Adverse Events in Oncology Pharmacy: Detection, Grading, and Actioning.Pharmacy (Basel, Switzerland) · 2025Review
- Temporal evolution of large language models (LLMs) in oncology.Journal of translational medicine · 2025Article
- Exploring Artificial Intelligence's Potential to Enhance Conventional Anticancer Drug Development.Drug development research · 2025Review
- Evaluating the performance of AI chatbots in responding to dental implant FAQs: A comparative study.BMC oral health · 2025Article
- Large language model processing capabilities of ChatGPT 4.0 to generate molecular tumor board recommendations-a critical evaluation on real world data.The oncologist · 2025Article
- Generative artificial intelligence, large language models and ChatGPT in musculoskeletal Oncology: Current applications and future potential.Journal of clinical orthopaedics and trauma · 2025Article
- Large language models enable tumor-type classification and localization of cancers of unknown primary from genomic data.Cell reports. Medicine · 2025Article
- Evaluating a Chatbot as a Companion for Patients With Breast Cancer: Collaborative Pilot Study.JMIR cancer · 2025Article
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
The development of large language models (LLMs) is a recent success in the field of generative artificial intelligence (AI). They are computer models able to perform a wide range of natural language processing tasks, including content generation, question answering, or language translation. In recent months, a growing number of studies aimed to assess their potential applications in the field of medicine, including cancer care. In this mini review, we described the present published evidence for using LLMs in oncology. All the available studies assessed ChatGPT, an advanced language model developed by OpenAI, alone or compared to other LLMs, such as Google Bard, Chatsonic, and Perplexity. Although ChatGPT could provide adequate information on the screening or the management of specific solid tumors, it also demonstrated a significant error rate and a tendency toward providing obsolete data. Therefore, an accurate, expert-driven verification process remains mandatory to avoid the potential for misinformation and incorrect evidence. Overall, although this new generative AI-based technology has the potential to revolutionize the field of medicine, including that of cancer care, it will be necessary to develop rules to guide the application of these tools to maximize benefits and minimize risks.
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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.