{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["22(1)"],"submitter":["Ji GW"],"pubmed_abstract":["<h4>Background</h4>Accurate prognosis assessment is essential for surgically resected intrahepatic cholangiocarcinoma (ICC) while published prognostic tools are limited by modest performance. We therefore aimed to establish a novel model to predict survival in resected ICC based on readily-available clinical parameters using machine learning technique.<h4>Methods</h4>A gradient boosting machine (GBM) was trained and validated to predict the likelihood of cancer-specific survival (CSS) on data from a Chinese hospital-based database using nested cross-validation, and then tested on the Surveillance, Epidemiology, and End Results (SEER) database. The performance of GBM model was compared with that of proposed prognostic score and staging system.<h4>Results</h4>A total of 1050 ICC patients (40"],"journal":["BMC cancer"],"pagination":["258"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8915487"],"repository":["biostudies-literature"],"pubmed_title":["Development and validation of a gradient boosting machine to predict prognosis after liver resection for intrahepatic cholangiocarcinoma."],"pmcid":["PMC8915487"],"pubmed_authors":["Li XC","Ji GW","Jiao CY","Wang XH","Xu ZG","Wang K"],"additional_accession":[]},"is_claimable":false,"name":"Development and validation of a gradient boosting machine to predict prognosis after liver resection for intrahepatic cholangiocarcinoma.","description":"<h4>Background</h4>Accurate prognosis assessment is essential for surgically resected intrahepatic cholangiocarcinoma (ICC) while published prognostic tools are limited by modest performance. We therefore aimed to establish a novel model to predict survival in resected ICC based on readily-available clinical parameters using machine learning technique.<h4>Methods</h4>A gradient boosting machine (GBM) was trained and validated to predict the likelihood of cancer-specific survival (CSS) on data from a Chinese hospital-based database using nested cross-validation, and then tested on the Surveillance, Epidemiology, and End Results (SEER) database. The performance of GBM model was compared with that of proposed prognostic score and staging system.<h4>Results</h4>A total of 1050 ICC patients (40","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Mar","modification":"2025-04-22T12:57:25.475Z","creation":"2025-04-06T00:24:22.898Z"},"accession":"S-EPMC8915487","cross_references":{"pubmed":["35277130"],"doi":["10.1186/s12885-022-09352-3"]}}