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Updated: Jun 9, 2025

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使用机器学习算法预测未经治疗的艾滋病毒患者的免疫风险:基于微量营养素和CD4/CD8比率逆转的决策树算法

Saurav Nayak1, Arvind Singh2, Manaswini Mangaraj1

  • 1Department of Biochemistry, All India Institute of Medical Sciences (AIIMS), Bhubaneswar, Bhubaneswar, India.

Frontiers in nutrition
|October 31, 2024
PubMed
概括

这项研究使用机器学习来分析艾滋病毒患者的微量元素,发现营养状况和免疫风险之间的联系. 这些发现表明微量营养素水平可以预测之前未接受治疗的个体的CD4/CD8比率逆转.

关键词:
CD4 / CD8 淋巴细胞 + + + +艾滋病病毒 艾滋病病毒 艾滋病病毒和是最重要的.机器学习和人工智能的含量是多少? 的含量是多少?微量营养素 微量营养素没有接受过治疗的患者.,和的使用情况.

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Causative Organism
The primary infectious agent causing tuberculosis is Mycobacterium tuberculosis, a slow-growing, acid-fast, aerobic rod that exhibits sensitivity to heat and ultraviolet light. Instances of Mycobacterium bovis and Mycobacterium avium contributing to the development of TB infection are rare.
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