ReviewJournal of pathology informatics2023
Current status of machine learning in thyroid cytopathology.
Review in Journal of pathology informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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
15 citing papers in PubMed.
- Validation of Digital Cytology for Primary Diagnosis Across a Range of Specimen Types.Cytopathology : official journal of the British Society for Clinical Cytology · 2026Article
- Harnessing artificial intelligence for enhanced veterinary diagnostics: A look to quality assurance, Part I Model development.Veterinary clinical pathology · 2025Review
- Can Artificial Intelligence Software be Utilised for Thyroid Multi-Disciplinary Team Outcomes?Clinical otolaryngology : official journal of ENT-UK ; official journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery · 2025Article
- Surveying the Digital Cytology Workflow in Italy: An Initial Report on AI Integration Across Key Professional Roles.Healthcare (Basel, Switzerland) · 2025Article
- Advancements in Digital Cytopathology Since COVID-19: Insights from a Narrative Review of Review Articles.Healthcare (Basel, Switzerland) · 2025Review
- Study on the Transformation Process of Thyroid Fine-Needle Aspiration Liquid-Based Cytology to Whole-Slide Image.Cytopathology : official journal of the British Society for Clinical Cytology · 2025Article
- Application progress of artificial intelligence in managing thyroid disease.Frontiers in endocrinology · 2025Review
- AI in Cytopathology: A Narrative Umbrella Review on Innovations, Challenges, and Future Directions.Journal of clinical medicine · 2024Review
- A novel computational pathology approach for identifying gene signatures prognostic of disease-free survival for papillary thyroid carcinomas.European journal of cancer (Oxford, England : 1990) · 2024Article
- Minimally invasive biopsy-based diagnostics in support of precision cancer medicine.Molecular oncology · 2024Review
- Review
- Machine Learning Model as a Useful Tool for Prediction of Thyroid Nodules Histology, Aggressiveness and Treatment-Related Complications.Journal of personalized medicine · 2023Article
- A Framework for Detecting Thyroid Cancer from Ultrasound and Histopathological Images Using Deep Learning, Meta-Heuristics, and MCDM Algorithms.Journal of imaging · 2023Article
- Trends in AI-powered Classification of Thyroid Neoplasms Based on Histopathology Images - a Systematic Review.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2023Article
- Cytopathology 2.0: How Artificial Intelligence Is Redefining the Future of Cytopathology.Journal of cytologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
The implementation of Digital Pathology has allowed the development of computational Pathology. Digital image-based applications that have received FDA Breakthrough Device Designation have been primarily focused on tissue specimens. The development of Artificial Intelligence-assisted algorithms using Cytology digital images has been much more limited due to technical challenges and a lack of optimized scanners for Cytology specimens. Despite the challenges in scanning whole slide images of cytology specimens, there have been many studies evaluating CP to create decision-support tools in Cytopathology. Among different Cytology specimens, thyroid fine needle aspiration biopsy (FNAB) specimens have one of the greatest potentials to benefit from machine learning algorithms (MLA) derived from digital images. Several authors have evaluated different machine learning algorithms focused on thyroid cytology in the past few years. The results are promising. The algorithms have mostly shown increased accuracy in the diagnosis and classification of thyroid cytology specimens. They have brought new insights and demonstrated the potential for improving future cytopathology workflow efficiency and accuracy. However, many issues still need to be addressed to further build on and improve current MLA models and their applications. To optimally train and validate MLA for thyroid cytology specimens, larger datasets obtained from multiple institutions are needed. MLAs hold great potential in improving thyroid cancer diagnostic speed and accuracy that will lead to improvements in patient management.
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.