Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Cross-Center Online Generalization Algorithm with Unadversarial Consistency for Fetal Heart Ultrasound View Recognition.

Journal of imaging informatics in medicine·2026
Same author

Clinicopathological Characteristics and Prognostic Significance of RET Fusion in Papillary Thyroid Carcinoma.

Head & neck·2026
Same author

Correction: Elevated IL-17A level is associated with poor overall survival following immune checkpoint inhibitors combined with targeted therapy in hepatocellular carcinoma with hyperbilirubinemia.

Frontiers in immunology·2026
Same author

Elevated IL-17A level is associated with poor overall survival following immune checkpoint inhibitors combined with targeted therapy in hepatocellular carcinoma with hyperbilirubinemia.

Frontiers in immunology·2026
Same author

CRISPR-Cas9-mediated homology-directed repair rescues the induced bone marrow failure in <i>Fancc</i> <sup>-/-</sup> mice.

Molecular therapy. Nucleic acids·2026
Same author

Development of a Novel Method to Detect AAV Vector Integration.

Viruses·2026

Related Experiment Video

Updated: Jan 8, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

470

An Interpretable Machine-Learning Model for Predicting Occult Central Lymph Node Metastasis in Papillary Thyroid

Zhongyu Wang1, Shangman Yang2,3, Yin Li4

  • 1Department of Head and Neck Surgery, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, P. R. China.

The Journal of Clinical Endocrinology and Metabolism
|December 11, 2025
PubMed
Summary

This study identifies RET fusion positivity as a key risk factor for occult lymph node metastasis in papillary thyroid cancer. A machine learning model aids in predicting this risk for better treatment planning.

Keywords:
RET fusioninterpretablemachine learningoccult lymph node metastasispapillary thyroid carcinomaprediction model

More Related Videos

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer
03:55

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer

Published on: June 9, 2023

911
Author Spotlight: A Model to Study the Systemic and Local Dynamics of CD8+ T Cells During LN Metastasis
07:45

Author Spotlight: A Model to Study the Systemic and Local Dynamics of CD8+ T Cells During LN Metastasis

Published on: January 26, 2024

2.6K

Related Experiment Videos

Last Updated: Jan 8, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

470
Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer
03:55

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer

Published on: June 9, 2023

911
Author Spotlight: A Model to Study the Systemic and Local Dynamics of CD8+ T Cells During LN Metastasis
07:45

Author Spotlight: A Model to Study the Systemic and Local Dynamics of CD8+ T Cells During LN Metastasis

Published on: January 26, 2024

2.6K

Area of Science:

  • Oncology
  • Medical Imaging
  • Genetics

Background:

  • Accurate prediction of occult lymph node metastasis (OLNM) in clinically lymph node negative (cN0) papillary thyroid carcinoma (PTC) is crucial for treatment optimization.
  • Strategies like thermal ablation and active surveillance require precise OLNM risk assessment.

Purpose of the Study:

  • To identify independent risk factors for OLNM in cN0 PTC.
  • To develop and evaluate machine learning models for predicting OLNM using clinical, ultrasonographic, and molecular features.

Main Methods:

  • Retrospective analysis of 961 cN0 PTC patients.
  • Multivariate logistic regression to identify risk factors.
  • Development and validation of eight machine learning models, including random forest, with SHAP for interpretability.

Main Results:

  • RET fusion and BRAF mutations identified as independent molecular risk factors for OLNM.
  • The random forest model showed optimal performance (AUC 0.906 training, 0.733 test).
  • Tumor size, age, and echogenic foci were top predictors identified by SHAP analysis.

Conclusions:

  • RET fusion positivity is a novel independent risk factor for OLNM in cN0 PTC.
  • The developed random forest model offers a framework for integrating diverse data for OLNM risk prediction.
  • A web calculator is available for practical application of the predictive model.