使用决策树来预测COVID病例数量:一个初学者教程
bioRxiv : the preprint server for biology
|January 8, 2024
概括
本模块介绍了机器学习 (ML) 和使用COVID数据进行生物医学研究教育的决策树. 它提供了一个可访问的,基于云的学习体验,培养未来科学家对机器学习的兴趣.
科学领域:
- 生物医学信息学 生物医学信息学
- 计算生物学 计算生物学
- 教育技术的教育技术
背景情况:
- 机器学习 (ML) 对于推动生物医学研究至关重要,有助于疾病的诊断,治疗和预防.
- COVID-19大流行突出了ML在公共卫生预测中的实用性.
- 在ML教育未来的研究人员和临床医生对于其在科学中的持续应用至关重要.
结论:
- 该学习模块有效地向生物学学生介绍机器学习基础知识和决策树概念.
- 基于云的平台促进了可访问和时间效率的ML教育.
- 这种方法显示了提高学生对机器学习研究兴趣的潜力.
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