2021
DOI: 10.3389/fmed.2021.635771
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Application of Machine Learning Algorithms to Predict Central Lymph Node Metastasis in T1-T2, Non-invasive, and Clinically Node Negative Papillary Thyroid Carcinoma

Abstract: Purpose: While there are no clear indications of whether central lymph node dissection is necessary in patients with T1-T2, non-invasive, clinically uninvolved central neck lymph nodes papillary thyroid carcinoma (PTC), this study seeks to develop and validate models for predicting the risk of central lymph node metastasis (CLNM) in these patients based on machine learning algorithms.Methods: This is a retrospective study comprising 1,271 patients with T1-T2 stage, non-invasive, and clinically node negative (c… Show more

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Cited by 53 publications
(74 citation statements)
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“… 13 , 27 Studies have already used machine learning technology to predict the development of diseases. 12 , 28 In this study, several widely used machine learning algorithms were developed and validated to predict the risk of BM in PCa patients. After the comparison of algorithms with several evaluation indicators, the XGB algorithm-based prediction model showed the best performance among these models.…”
Section: Discussionmentioning
confidence: 99%
“… 13 , 27 Studies have already used machine learning technology to predict the development of diseases. 12 , 28 In this study, several widely used machine learning algorithms were developed and validated to predict the risk of BM in PCa patients. After the comparison of algorithms with several evaluation indicators, the XGB algorithm-based prediction model showed the best performance among these models.…”
Section: Discussionmentioning
confidence: 99%
“…Zhu et al. ( 46 ) applied six machine learning algorithms coupled with preoperative clinical characteristics and intraoperative information to develop prediction models for CLNM. Yang et al.…”
Section: Discussionmentioning
confidence: 99%
“…This individualized model has satisfied the requirements of precision medicine development and can be used by doctors and patients easily.Many studies have been conducted on this topic(44)(45)(46)(47)(48). Zhu et al(46) applied six machine learning algorithms coupled with preoperative clinical characteristics and intraoperative information to develop prediction models for CLNM. Yang et al(47) developed a multicenter nomogram with internal and external validation set C-index values of 0.854 and 0.825, respectively.…”
mentioning
confidence: 99%
“…Special attention should be paid to the increase in the preoperative detection of lymph node metastases. To achieve it, several studies have recently proposed some preoperative algorithms of management (55)(56)(57).…”
Section: Discussionmentioning
confidence: 99%