Machine Learning for Predicting Distant Metastasis of Medullary Thyroid Carcinoma Using the SEER Database.

Objectives: We aimed to establish an effective machine learning (ML) model for predicting the risk of distant metastasis (DM) in medullary thyroid carcinoma (MTC).

Methods: Demographic data of MTC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database of the National Institutes of Health between 2004 and 2015 to develop six ML algorithm models. Models were evaluated based on accuracy, precision, recall rate, 1-score, and area under the receiver operating characteristic curve (AUC).

Correlation of LARP1 and E-cadherin expression with prognosis of intrahepatic cholangiocarcinoma.

Objective: The abnormal expression of LARP1 and E-cadherin (E-cad) is related to tumor occurrence and metastasis. Our study analyzed the expression of LARP1 and E-cad in intrahepatic cholangiocarcinoma (ICC) and investigated the prognostic value of the two proteins.

Methods: Immunohistochemistry was performed to detect the expression of LARP1 and E-cad in 50 ICC clinical specimens with adjacent normal tissues and 20 normal bile duct tissues.