Development of machine learning models for patients in the high intrahepatic cholangiocarcinoma incidence age group.

Journal: BMC geriatrics
PMID: 38918710

Abstract

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) has a poor prognosis and is understudied. Based on the clinical features of patients with ICC, we constructed machine learning models to understand their importance on survival and to accurately determine patient prognosis, aiming to develop reference values to guide physicians in developing more effective treatment plans.

Authors

  • Jie Shen
    Anhui Provincial Center for Drug Clinical Evaluation, Yijishan Hospital, Wannan Medical College, Wuhu, Anhui 241001, China; Pharmacy School, Wannan Medical College, Wuhu, Anhui 241002, China; Department of Clinical Pharmacy, Yijishan Hospital, Wannan Medical College, Wuhu, Anhui 241001, China; Anhui Provincial Engineering Research Center for Polysaccharides Drugs, Wannan Medical College, Wuhu, Anhui 241001, China.
  • Dashuai Yang
    Dept of hepatobiliary surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, 430060, China.
  • Yu Zhou
    Department of Biospectroscopy, Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany.
  • Junpeng Pei
    Dept of hepatobiliary surgery, 521 Hospital of Norinco Group, Xi'an, Shaanxi, 710061, China.
  • Zhongkai Wu
    Department of Cardiac Surgery, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China. Electronic address: wuzhk@mail.sysu.edu.cn.
  • Xin Wang
    Key Laboratory of Bio-based Material Science & Technology (Northeast Forestry University), Ministry of Education, Harbin 150040, China.
  • Kailiang Zhao
    Dept of hepatobiliary surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, 430060, China. zhaokl1983@whu.edu.cn.
  • Youming Ding
    Dept of hepatobiliary surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, 430060, China. dingym@whu.edu.cn.

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