ArticleJournal of healthcare engineering2022
Construction of a Diagnostic Model for Lymph Node Metastasis of the Papillary Thyroid Carcinoma Using Preoperative Ultrasound Features and Imaging Omics.
Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A clinically practical machine learning nomogram for preoperative CLNM prediction in PTMC: tumor-capsule distance and D2-40 evidence.Frontiers in oncology · 2026Article
- Combined model integrating clinical, radiomics, BRAFGland surgery · 2024Article
- Predictors of lateral lymph node metastasis and skip metastasis in patients with papillary thyroid microcarcinoma.Frontiers in endocrinology · 2024Article
- Construction and validation of a diagnostic model for high-risk papillary thyroid microcarcinoma.Frontiers in endocrinology · 2024Article
- Risk factor analysis and prediction model for papillary thyroid carcinoma with lymph node metastasis.Frontiers in endocrinology · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, we mainly adopted 337 patients who had undergone the surgery on lymph node metastasis of papillary thyroid carcinoma (PTC) as the sample population. In order to provide clinical reference for the intelligent decision-making in treatment plan and improvement of prognosis, we utilized ultrasound features and imaging features to construct five early diagnosis models for patients based on the ultrasound features, imaging features, and combined features. The model integrated with broad learning system (BLS) showed the best performance, with the area under the curve (AUC) of 0.857 (95% confidence interval (CI): 0.811-0.902)) and the accuracy of 0.805 (95% CI: 0.759-0.850). For demographic and clinical features, the prediction effect was also good, with the AUC more than 0.700.
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