ArticleBMC cancer2023
Deep learning-based multifeature integration robustly predicts central lymph node metastasis in papillary thyroid cancer.
Article in BMC cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.
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Who cites it
30 citing papers in PubMed, 2 syntheses or guidelines pooled it, 61 citations in OpenAlex.
- Diagnostic performance of machine learning and deep learning algorithms for thyroid cancer metastasis: a systematic review and meta-analysis.BMC medical informatics and decision making · 2025Pooled it
- Pooled it
- Cervical lymph node metastasis prediction from papillary thyroid carcinoma US videos: a prospective multicenter study.BMC medicine · 2024Trial
- Artificial intelligence in thyroid nodules and cancer: clinical validation and real-world performance.Endocrine connections · 2026Article
- Deep learning-based multimodal radiopathomics for preoperative prediction of lymph node metastasis in papillary thyroid carcinoma.Scientific reports · 2026Article
- Molecular Determinants of Thyroid Cancer Progression: Thyroid Hormone Signaling, the BRAF/MAPK Pathway, and Emerging miRNA Biomarkers.Biomedicines · 2026Review
- Syncretic Grad-CAM Integrated ViT-CNN Hybrids with Inherent Explainability for Early Thyroid Cancer Diagnosis from Ultrasound.Diagnostics (Basel, Switzerland) · 2026Article
- Dual-channel ultrasonic images empowered deep learning: significantly improving prediction of occult central lymph node metastases in solitary papillary thyroid microcarcinoma.Radiology and oncology · 2026Article
- Adaptive Bandelet Transform and Transfer Learning for Geometry-Aware Thyroid Cancer Ultrasound Classification.Diagnostics (Basel, Switzerland) · 2026Article
- Utilizing the transformer mechanism to predict cervical lymph node metastasis in patients with papillary thyroid carcinoma.PloS one · 2026Article
- Machine Learning: A Multicenter Study on Predicting Lateral Lymph Node Metastasis in cN0 Papillary Thyroid Carcinoma.The Journal of clinical endocrinology and metabolism · 2025Article
- Positive preoperative circulating tumor cells level associated with lymph node metastasis in papillary thyroid carcinoma patients with capsular invasion.World journal of surgical oncology · 2025Article
- Machine Learning for Thyroid Cancer Detection, Presence of Metastasis, and Recurrence Predictions-A Scoping Review.Cancers · 2025Review
- Nomograms for predicting cervical central lymph node metastases and high-volume cervical central lymph node metastases in papillary thyroid carcinoma.Gland surgery · 2025Article
- Preoperative circulating tumor cells level is associated with lymph node metastasis in patients with unifocal papillary thyroid carcinoma.World journal of surgical oncology · 2025Article
- Development and validation of a dynamic nomogram for predicting central lymph node metastasis in papillary thyroid carcinoma patients based on clinical and ultrasound features.Quantitative imaging in medicine and surgery · 2025Article
- Multifactorial risk stratification for central lymph node metastasis in papillary thyroid carcinoma: a predictive model integrating clinical and tumor characteristics.Frontiers in oncology · 2025Article
- A predictive nomogram of thyroid nodules based on deep learning ultrasound image analysis.Frontiers in endocrinology · 2025Article
- Thyroid nodule and lymph node metastasis assessment from ultrasound images using deep learning.Frontiers in neuroscience · 2025Article
- Multimodal MRI Deep Learning for Predicting Central Lymph Node Metastasis in Papillary Thyroid Cancer.Cancers · 2024Article
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
backgroundFew highly accurate tests can diagnose central lymph node metastasis (CLNM) of papillary thyroid cancer (PTC). Genetic sequencing of tumor tissue has allowed the targeting of certain genetic variants for personalized cancer therapy development.
methodsThis study included 488 patients diagnosed with PTC by ultrasound-guided fine-needle aspiration biopsy, collected clinicopathological data, analyzed the correlation between CLNM and clinicopathological features using univariate analysis and binary logistic regression, and constructed prediction models.
resultsBinary logistic regression analysis showed that age, maximum diameter of thyroid nodules, capsular invasion, and BRAF V600E gene mutation were independent risk factors for CLNM, and statistically significant indicators were included to construct a nomogram prediction model, which had an area under the curve (AUC) of 0.778. A convolutional neural network (CNN) prediction model built with an artificial intelligence (AI) deep learning algorithm achieved AUCs of 0.89 in the training set and 0.78 in the test set, which indicated a high prediction efficacy for CLNM. In addition, the prediction models were validated in the subclinical metastasis and clinical metastasis groups with high sensitivity and specificity, suggesting the broad applicability of the models. Furthermore, CNN prediction models were constructed for patients with nodule diameters less than 1 cm. The AUCs in the training set and test set were 0.87 and 0.76, respectively, indicating high prediction efficacy.
conclusionsThe deep learning-based multifeature integration prediction model provides a reference for the clinical diagnosis and treatment of PTC.
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