Breaking Barriers in Thyroid Cytopathology: Harnessing Deep Learning for Accurate Diagnosis
This study provides a feasibility analysis for thyroid cytopathology classification and visual interpretability for AI diagnosis, suggesting potential improvements in patient outcomes and reductions in healthcare costs.
Authors
- Dong Joo Kang
- Sabyasachi Chakraborty (ORCID: https://orcid.org/0000-0003-1344-296X)
- Seo Young Oh
- Yong‐Moon Lee (ORCID: https://orcid.org/0000-0002-4302-9263)
- Jae Hyun Park (ORCID: https://orcid.org/0000-0002-7748-8492)
- Hyeong Ju Kwon (ORCID: https://orcid.org/0000-0003-1615-7152)
Institutions
- Yonsei University (KR)
- Wonju Severance Christian Hospital (KR)
- Dankook University (KR)
Publication Details
- Journal
- Bioengineering
- Published
- 2025-03-14
- DOI
- https://doi.org/10.3390/bioengineering12030293
- Citations
- 1
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 2.48