ReviewThe Lancet regional health. Europe2024
Artificial intelligence in oncology: ensuring safe and effective integration of language models in clinical practice.
Review in The Lancet regional health. Europe, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis 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
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence and Decision-Making in Oncology: A Review of Ethical, Legal, and Informed Consent Challenges.Current oncology reports · 2025Pooled it
- Applying clinical natural language processing to lung cancer in Spain: a terminology-based panel approach.ESMO real world data and digital oncology · 2026Article
- Review
- Artificial intelligence integrated multi-omics and multimodal studies promote the efficacy of neoadjuvant chemotherapy in breast cancer: opportunities, challenges, and future perspectives.Breast cancer research : BCR · 2026Review
- [Research progress in artificial intelligence for the diagnosis and management of diseases in preterm infants].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2026Review
- A new era of precision diagnosis and treatment for lung cancer: artificial intelligence-driven multimodal data integration and clinical applications.Cell death & disease · 2026Review
- The role of AI in oncology: present applications and future horizons.NPJ precision oncology · 2026Review
- Artificial Intelligence Language Models in Oncology: A Cross-Sectional Analysis of Published Studies.Cureus · 2026Review
- A context-augmented large language model for accurate precision oncology medicine recommendations.Cancer cell · 2026Article
- Convergence of machine learning and genomics for precision oncology.Nature reviews. Cancer · 2026Review
- Applications of Artificial Intelligence Technologies in Nursing for Noncommunicable Chronic Diseases: A Scoping Review.Journal of nursing management · 2026Article
- A roadmap for medical large language models: a review of foundations, applications, and challenges.Military Medical Research · 2026Review
- Advancements in artificial intelligence for cancer diagnosis and prognosis prediction: current applications and emerging opportunities.Frontiers in cell and developmental biology · 2026Review
- A novel evaluation benchmark for medical LLMs illuminating safety and effectiveness in clinical domains.NPJ digital medicine · 2025Article
- Development and validation of a pre-trained language model for neonatal morbidities: a retrospective, multicentre, prognostic study.The Lancet. Digital health · 2025Article
- Enabling Just-in-Time Clinical Oncology Analysis With Large Language Models: Feasibility and Validation Study Using Unstructured Synthetic Data.JMIR medical informatics · 2025Article
- Scaling up biomedical vision-language models: Fine-tuning, instruction tuning, and multi-modal learning.Journal of biomedical informatics · 2025Article
- Using Artificial Intelligence to Develop Clinical Decision Support Systems-The Evolving Road of Personalized Oncologic Therapy.Diagnostics (Basel, Switzerland) · 2025Article
- Review
- Application of artificial intelligence in medical imaging for tumor diagnosis and treatment: a comprehensive approach.Discover oncology · 2025Review
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
In this Personal View, we address the latest advancements in automatic text analysis with artificial intelligence (AI) in medicine, with a focus on its implications in aiding treatment decisions in medical oncology. Acknowledging that a majority of hospital medical content is embedded in narrative format, natural language processing has become one of the most dynamic research fields for developing clinical decision support tools. In addition, large language models have recently reached unprecedented performance, notably when answering medical questions. Emerging applications include prognosis estimation, treatment recommendations, multidisciplinary tumor board recommendations and matching patients to recruiting clinical trials. Altogether, we advocate for a forward-looking approach in which the community efficiently initiates global prospective clinical evaluations of promising AI-based decision support systems. Such assessments will be essential to validate and evaluate potential biases, ensuring these innovations can be effectively and safely translated into practical tools for oncological practice. We are at a pivotal moment, where continued advancements in patient care must be pursued with scientific rigor.
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.