Predicting hospitalization costs for pulmonary tuberculosis patients based on machine learning.

Journal: BMC infectious diseases
PMID: 39198742

Abstract

BACKGROUND: Pulmonary tuberculosis (PTB) is a prevalent chronic disease associated with a significant economic burden on patients. Using machine learning to predict hospitalization costs can allocate medical resources effectively and optimize the cost structure rationally, so as to control the hospitalization costs of patients better.

Authors

  • Shiyu Fan
    Department of Radiology, The First People's Hospital of Kashi (Kashgar) Prefecture, China.
  • Abudoukeyoumujiang Abulizi
    The First People's Hospital of Kashi, Xinjiang, China.
  • Yi You
    Nanjing University of Chinese Medicine, Nanjing, China.
  • Chencui Huang
    Department of Research Collaboration, R&D Center, Beijing Deepwise & League of PHD Technology Co., Ltd., Beijing, China.
  • Yasen Yimit
    Department of Radiology, The First People's Hospital of Kashi (Kashgar) Prefecture, Xinjiang, China, 844000; Xinjiang Key Laboratory of Artificial Intelligence assisted Imaging Diagnosis, Kashi (Kashgar), China, 844000.
  • Qiange Li
    Department of Preventive Healthcare, Shihezi University, Shihezi, 832000, China.
  • Xiaoguang Zou
    The First People's Hospital of Kashi, Xinjiang, China.
  • Mayidili Nijiati
    The First People's Hospital of Kashi, Xinjiang, China.

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