ReviewAdvances in therapy2025
The Limitations of Artificial Intelligence in Head and Neck Oncology.
Review in Advances in therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning based prediction of recurrence in oral tongue cancer: a systematic review with quantitative synthesis.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026Pooled it
- X-CART: a multimodal real-world data pipeline for explainable AI-driven patient navigation in radiation oncology.ESMO real world data and digital oncology · 2026Article
- Comparing the text-based diagnostic reasoning performance of emergency medicine physicians and large language models in both definitive and differential diagnoses using standardized clinical vignettes: a preliminary study.International journal of emergency medicine · 2026Article
- Performance of Machine Learning Models for Prognosis Prediction in Oral Cavity Squamous Cell Carcinoma: A Systematic Review.Cancers · 2026Review
- Beyond Couch Correction in Head and Neck Radiotherapy: A Narrative Review of Action-Oriented Positioning Management.Cancers · 2026Review
- Educational Frameworks for Diagnostic Decision-Making in AI-Enhanced Head and Neck Pathology.Head and neck pathology · 2026Review
- Artificial Intelligence in Head and Neck Surgical Oncology: A State-of-the-Art Review.Journal of clinical medicine · 2026Review
- HPV Detection in Oropharyngeal Cancer: A Narrative Review of Diagnostic and Emerging Molecular Approaches.Diagnostics (Basel, Switzerland) · 2026Review
- BRAF inhibitor resistance in melanoma: from resistance mechanisms to therapeutic innovations.Molecular biomedicine · 2026Review
- Precision Diagnosis in Cutaneous Head and Neck Squamous Cell Carcinoma.Biomedicines · 2026Review
- AI and human expertise in cancer care - striving for synergy.Nature reviews. Clinical oncology · 2026Article
- Artificial Intelligence Approaches to Predict Postoperative Length of Hospital Stay in Head and Neck Cancer Patients: A Systematic Review.Diagnostics (Basel, Switzerland) · 2026Review
- The tongue may not move, but the voice will: preoperative AI voice cloning for identity preservation in major glossectomy - a prospective feasibility study.Frontiers in oncology · 2026Article
- Predicting Reintubation in Postoperative Pediatric Cardiac Surgery: A Machine Learning Approach.Annals of cardiac anaesthesia · 2026Article
- Radiomic-Based Machine Learning Classifiers for HPV Status Prediction in Oropharyngeal Cancer: A Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2025Review
- From Radical Resection to Precision Surgery: Integrating Diagnostic Biomarkers, Radiomics-Based Predictive Models, and Perioperative Systemic Therapy in Head and Neck Oncology.Diagnostics (Basel, Switzerland) · 2025Review
- Evaluation of Deep Learning Convolutional Neural Networks for Classification of Carcinoma Ex Pleomorphic Adenoma and Pleomorphic Adenoma in Whole-Slide Images.Head and neck pathology · 2025Article
- Micrometastasis and Isolated Tumor Cells in Oral Squamous Cell Carcinoma: Refining Nodal Staging with Emerging Technologies.Head and neck pathology · 2025Review
- Article
- Assistive, not autonomous: Generative artificial intelligence in head and neck cancer care - A scoping review.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is revolutionizing head and neck oncology, offering innovations in tumor detection, treatment planning, and patient management. However, its integration into clinical practice is hindered by several limitations. These include clinician mistrust due to a lack of understanding of AI mechanisms, biases in algorithm development, and the potential over-reliance on technology, which may undermine clinical expertise. Data-related challenges, such as inconsistent quality and limited representativeness of datasets, further complicate AI's application. Ethical, legal, and privacy concerns also pose significant barriers. Addressing these issues through transparent AI systems, clinician education, and clear regulations is essential for ensuring responsible, equitable use in head and neck oncology. This manuscript explores the limitations of AI in head and neck oncology.
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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.