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Accepted for/Published in: JMIR Medical Informatics

Date Submitted: Oct 28, 2020
Open Peer Review Period: Oct 28, 2020 - Nov 2, 2020
Date Accepted: Nov 2, 2020
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Correction: A Novel Approach to Assessing Differentiation Degree and Lymph Node Metastasis of Extrahepatic Cholangiocarcinoma: Prediction Using a Radiomics-Based Particle Swarm Optimization and Support Vector Machine Model

Yao X, Huang X, Yang C, Hu A, Zhou G, Lei J, Shu J

Correction: A Novel Approach to Assessing Differentiation Degree and Lymph Node Metastasis of Extrahepatic Cholangiocarcinoma: Prediction Using a Radiomics-Based Particle Swarm Optimization and Support Vector Machine Model

JMIR Med Inform 2021;9(1):e25337

DOI: 10.2196/25337

PMID: 33439852

PMCID: 7840293

Correction: A Novel Approach to Assessing Differentiation Degree and Lymph Node Metastasis of Extrahepatic Cholangiocarcinoma: Prediction Using a Radiomics-Based Particle Swarm Optimization and Support Vector Machine Model

  • Xiaopeng Yao; 
  • Xinqiao Huang; 
  • Chunmei Yang; 
  • Anbin Hu; 
  • Guangjin Zhou; 
  • Jianbo Lei; 
  • Jian Shu

Background:

N/A

Objective:

N/A

Methods:

N/A

Results:

N/A

Conclusions:

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 Citation

Please cite as:

Yao X, Huang X, Yang C, Hu A, Zhou G, Lei J, Shu J

Correction: A Novel Approach to Assessing Differentiation Degree and Lymph Node Metastasis of Extrahepatic Cholangiocarcinoma: Prediction Using a Radiomics-Based Particle Swarm Optimization and Support Vector Machine Model

JMIR Med Inform 2021;9(1):e25337

DOI: 10.2196/25337

PMID: 33439852

PMCID: 7840293

Per the author's request the PDF is not available.

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