ArticleNature communications2025
Explainable multimodal deep learning for predicting thyroid cancer lateral lymph node metastasis using ultrasound imaging.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Peritumoral ultrasound-driven multimodal AI model for predicting lymphovascular space invasion and prognosis in cervical cancer.Abdominal radiology (New York) · 2026Article
- DSDFF-YOLO: an automated computer-aided diagnostic method for post-therapy radioiodine whole-body scan.European radiology · 2026Article
- Development and Validation of a Picture Archiving and Communication System-Integrated Artificial Intelligence for Predicting Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma.Journal of imaging informatics in medicine · 2026Article
- Development and Validation of an Interpretable Machine Learning Model for Predicting Early Pulmonary Metastasis Risk in Osteosarcoma.Cancer medicine · 2026Article
- Genomics and Multi-Omics to Guide Clinical Management in Thyroid Cancer.International journal of molecular sciences · 2026Review
- Multi-Modal Ultrasound-Based Prognostic Model for Diffuse Large B-Cell Lymphoma with Predominantly Superficial Lymph Node Involvement.Diagnostics (Basel, Switzerland) · 2026Article
- Reimagining Nodal Staging in Colorectal Cancer: Toward a Novel Non-Invasive Imaging Approach.Cancers · 2026Review
- A multimodal feature disentanglement model for lymphadenopathy diagnosis based on BUS and CDFI ultrasound videos: a retrospective, prospective, multicenter study.European radiology · 2026Article
- Development and validation of an ultrasound-based predictive model for central lymph node metastasis in papillary thyroid carcinoma with peripheral calcification.Gland surgery · 2026Article
- iPalmT: a new paradigm for palmitoyltransferase discovery via end-to-end deep learning.Oncogene · 2026Article
- Thyroid Metastasis as the Initial Presentation of Occult Breast Carcinoma: A Case Report.Cureus · 2026Article
- ThyroFusion: A Multi-modal Deep Learning Framework Integrating Vision and Language for Thyroid Nodule Malignancy Risk Assessment.Journal of imaging informatics in medicine · 2026Article
- Dual nomograms to predict central and lateral cervical lymph node metastasis in papillary thyroid carcinoma with Hashimoto's thyroiditis: a two-cohort study.Frontiers in endocrinology · 2026Article
- Editorial: Artificial intelligence in multi-omics: advancing tumor metastasis prediction and mechanism analysis.Frontiers in cell and developmental biology · 2026Article
- Comprehensive analysis of carotid triangle lymph node metastasis in papillary thyroid carcinoma.Frontiers in endocrinology · 2026Article
- A dual-branch deep learning framework with Mask-Guided Attention for thyroid nodule classification in ultrasound images.Frontiers in medicine · 2026Article
- Development and validation of a machine learning model for predicting high-risk distant metastatic recurrence in differentiated thyroid cancer.Frontiers in medicine · 2026Article
- Utilizing the transformer mechanism to predict cervical lymph node metastasis in patients with papillary thyroid carcinoma.PloS one · 2026Article
- An interpretable machine learning-based approach: development, validation, and clinical utility for distant metastasis prediction in PTC.Frontiers in endocrinology · 2026Article
- Quantitative Analysis of the Impact of Region of Interest Information on Deep Learning Algorithms for Thyroid Ultrasound Imaging.IEEE open journal of engineering in medicine and biology · 2026Article
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Authors and funding
11 authors.
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Abstract
Preoperative prediction of lateral lymph node metastasis is clinically crucial for guiding surgical strategy and prognosis assessment, yet precise prediction methods are lacking. We therefore develop Lateral Lymph Node Metastasis Network (LLNM-Net), a bidirectional-attention deep-learning model that fuses multimodal data (preoperative ultrasound images, radiology reports, pathological findings, and demographics) from 29,615 patients and 9836 surgical cases across seven centers. Integrating nodule morphology and position with clinical text, LLNM-Net achieves an Area Under the Curve (AUC) of 0.944 and 84.7% accuracy in multicenter testing, outperforming human experts (64.3% accuracy) and surpassing previous models by 7.4%. Here we show tumors within 0.25 cm of the thyroid capsule carry >72% metastasis risk, with middle and upper lobes as high-risk regions. Leveraging location, shape, echogenicity, margins, demographics, and clinician inputs, LLNM-Net further attains an AUC of 0.983 for identifying high-risk patients. The model is thus a promising for tool for preoperative screening and risk stratification.
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