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With the increasing number of elderly patients with cognitive impairment due to cerebral small vessel disease (CSVD) and the integration of computer technology in the medical field, there is an urgent need for more effective data analysis methods to reveal the relationships among different medical data features, helping clinicians better understand the disease mechanisms and influencing factors. The wide availability of decision trees in clinical research makes it more feasible to mine disease risk factors. Therefore, a decision tree model is constructed to predict the risk of cognitive impairment.

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A Prediction Model for Assessing the Risk of Cognitive Dysfunction in Elderly Patients with Cerebral Small Vessel Disease Was Developed Using Decision Tree Algorithms

  • 会议论文

  • 发表日期：

    2026年

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  • Wang Xiaojie,
  • Wang Wenxiu,
  • Zhang Qiang,
  • Li Xin,
  • Pang Yi,
  • Zhang Hong

摘要

With the increasing number of elderly patients with cognitive impairment due to cerebral small vessel disease (CSVD) and the integration of computer technology in the medical field, there is an urgent need for more effective data analysis methods to reveal the relationships among different medical data features, helping clinicians better understand the disease mechanisms and influencing factors. The wide availability of decision trees in clinical research makes it more feasible to mine disease risk factors. Therefore, a decision tree model is constructed to predict the risk of cognitive impairment.