ReviewCancers2023
The Use of Artificial Intelligence in the Diagnosis and Classification of Thyroid Nodules: An Update.
Review in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 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
24 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Exploring the role of artificial intelligence in chemotherapy development, cancer diagnosis, and treatment: present achievements and future outlook.Frontiers in oncology · 2025Pooled it
- From Bench-to-Bedside: How Artificial Intelligence is Changing Thyroid Nodule Diagnostics, a Systematic Review.The Journal of clinical endocrinology and metabolism · 2024Pooled it
- Training the diagnostic artificial intelligence in thyroid sonography: how well is deep learning truly learning?Updates in surgery · 2026Article
- Diagnostic performance of multimodal ultrasound-based deep learning models in differentiating benign and malignant thyroid nodules.Frontiers in oncology · 2026Article
- Hyperthyroidism-Related Epithelial Hyperplasia as a Potential Pitfall of Thyroid Cytology: Institutional Cytomorphological Analysis of Histologically Verified Cases.Acta cytologica · 2026Article
- An interpretable multimodal machine learning model for predicting malignancy of thyroid nodules in low-resource scenarios.BMC endocrine disorders · 2025Article
- Current AI technologies in cancer diagnostics and treatment.Molecular cancer · 2025Review
- Diagnostic value of deep learning of multimodal imaging of thyroid for TI-RADS category 3-5 classification.Endocrine · 2025Article
- Surveying the Digital Cytology Workflow in Italy: An Initial Report on AI Integration Across Key Professional Roles.Healthcare (Basel, Switzerland) · 2025Article
- Comparing ChatGPT 4.0's Performance in Interpreting Thyroid Nodule Ultrasound Reports Using ACR-TI-RADS 2017: Analysis Across Different Levels of Ultrasound User Experience.Diagnostics (Basel, Switzerland) · 2025Article
- Review
- Advancing thyroid diagnosis: integrating AI-driven CAD framework with numerical data and ultrasound images.PeerJ. Computer science · 2025Article
- Subtypes detection of papillary thyroid cancer from methylation assay via Deep Neural Network.Computational and structural biotechnology journal · 2025Article
- AI in Cytopathology: A Narrative Umbrella Review on Innovations, Challenges, and Future Directions.Journal of clinical medicine · 2024Review
- Progress Achieved, Landmarks, and Future Concerns in Biomedical and Health Informatics.Healthcare (Basel, Switzerland) · 2024Review
- Review
- BRAF Detection in FNAC Combined with Semi-QuantitativeDiagnostics (Basel, Switzerland) · 2024Article
- Rates of diagnostic and therapeutic procedures in a cohort of patients undergoing first endocrine consultation for thyroid nodular disease.Endocrine · 2024Observational
- Comparative Cyto-Histological Genetic Profile in a Series of Differentiated Thyroid Carcinomas.Diagnostics (Basel, Switzerland) · 2024Article
- Machine Learning Model as a Useful Tool for Prediction of Thyroid Nodules Histology, Aggressiveness and Treatment-Related Complications.Journal of personalized medicine · 2023Article
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
Abstract
The incidence of thyroid nodules diagnosed is increasing every year, leading to a greater risk of unnecessary procedures being performed or wrong diagnoses being made. In our paper, we present the latest knowledge on the use of artificial intelligence in diagnosing and classifying thyroid nodules. We particularly focus on the usefulness of artificial intelligence in ultrasonography for the diagnosis and characterization of pathology, as these are the two most developed fields. In our search of the latest innovations, we reviewed only the latest publications of specific types published from 2018 to 2022. We analyzed 930 papers in total, from which we selected 33 that were the most relevant to the topic of our work. In conclusion, there is great scope for the use of artificial intelligence in future thyroid nodule classification and diagnosis. In addition to the most typical uses of artificial intelligence in cancer differentiation, we identified several other novel applications of artificial intelligence during our review.
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.