{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T11:01:19Z","timestamp":1771066879810,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,9,15]],"date-time":"2024-09-15T00:00:00Z","timestamp":1726358400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Beijing Municipal Science &amp; Technology Commission","award":["Z171100000417056"],"award-info":[{"award-number":["Z171100000417056"]}]},{"name":"Beijing Municipal Science &amp; Technology Commission","award":["GZKJ-KJXX-QTHT-20230626"],"award-info":[{"award-number":["GZKJ-KJXX-QTHT-20230626"]}]},{"name":"Key Support Project of Guo Zhong Health Care of China General Technology Group","award":["Z171100000417056"],"award-info":[{"award-number":["Z171100000417056"]}]},{"name":"Key Support Project of Guo Zhong Health Care of China General Technology Group","award":["GZKJ-KJXX-QTHT-20230626"],"award-info":[{"award-number":["GZKJ-KJXX-QTHT-20230626"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>(1) Background: This study seeks to employ a machine learning (ML) algorithm to forecast the risk of distant metastasis (DM) in patients with T1 and T2 gallbladder cancer (GBC); (2) Methods: Data of patients diagnosed with T1 and T2 GBC was obtained from SEER, encompassing the period from 2004 to 2015, were utilized to apply seven ML algorithms. These algorithms were appraised by the area under the receiver operating characteristic curve (AUC) and other metrics; (3) Results: This study involved 4371 patients in total. Out of these patients, 764 (17.4%) cases progressed to develop DM. Utilizing a logistic regression (LR) model to identify independent risk factors for DM of gallbladder cancer (GBC). A nomogram has been developed to forecast DM in early T-stage gallbladder cancer patients. Through the evaluation of different models using relevant indicators, it was discovered that Random Forest (RF) exhibited the most outstanding predictive performance; (4) Conclusions: RF has demonstrated high accuracy in predicting DM in gallbladder cancer patients, assisting clinical physicians in enhancing the accuracy of diagnosis. This can be particularly valuable for improving patient outcomes and optimizing treatment strategies. We employ the RF algorithm to construct the corresponding web calculator.<\/jats:p>","DOI":"10.3390\/bioengineering11090927","type":"journal-article","created":{"date-parts":[[2024,9,18]],"date-time":"2024-09-18T01:52:31Z","timestamp":1726624351000},"page":"927","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Machine Learning Algorithm for Predicting Distant Metastasis of T1 and T2 Gallbladder Cancer Based on SEER Database"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2530-0590","authenticated-orcid":false,"given":"Zhentian","family":"Guo","sequence":"first","affiliation":[{"name":"Department of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, Beijing 100073, China"},{"name":"Key Laboratory of Geriatrics (Hepatobiliary Diseases) of China General Technology Group, Beijing 100073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0797-7100","authenticated-orcid":false,"given":"Zongming","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, Beijing 100073, China"},{"name":"Key Laboratory of Geriatrics (Hepatobiliary Diseases) of China General Technology Group, Beijing 100073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Limin","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, Beijing 100073, China"},{"name":"Key Laboratory of Geriatrics (Hepatobiliary Diseases) of China General Technology Group, Beijing 100073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, Beijing 100073, China"},{"name":"Key Laboratory of Geriatrics (Hepatobiliary Diseases) of China General Technology Group, Beijing 100073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhuo","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, Beijing 100073, China"},{"name":"Key Laboratory of Geriatrics (Hepatobiliary Diseases) of China General Technology Group, Beijing 100073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, Beijing 100073, China"},{"name":"Key Laboratory of Geriatrics (Hepatobiliary Diseases) of China General Technology Group, Beijing 100073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Qi","sequence":"additional","affiliation":[{"name":"Department of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, Beijing 100073, China"},{"name":"Key Laboratory of Geriatrics (Hepatobiliary Diseases) of China General Technology Group, Beijing 100073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinqiu","family":"Feng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geriatrics (Hepatobiliary Diseases) of China General Technology Group, Beijing 100073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peijie","family":"Yao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geriatrics (Hepatobiliary Diseases) of China General Technology Group, Beijing 100073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiming","family":"Yuan","sequence":"additional","affiliation":[{"name":"Department of General Surgery, Beijing Electric Power Hospital, State Grid Corporation of China, Capital Medical University, Beijing 100073, China"},{"name":"Key Laboratory of Geriatrics (Hepatobiliary Diseases) of China General Technology Group, Beijing 100073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"12297","DOI":"10.1007\/s00432-023-05116-z","article-title":"Effect of different surgical options on the long-term survival of stage I gallbladder cancer: A retrospective study based on SEER database and Chinese Multi-institutional Registry","volume":"149","author":"Ji","year":"2023","journal-title":"J. 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