知识图及其在神经和精神疾病研究中的应用
Qizheng Wang1, Fan Yang1, Lijie Quan1
1School of Biomedical Engineering, Tianjin Medical University, Tianjin, China.
Frontiers in psychiatry
|April 2, 2025
概括
知识图 (KG) 提供了一种强大的方法来分析神经和精神疾病的复杂数据. 这篇评论探讨了它们在理解阿尔茨海默氏症和抑郁症等疾病方面的应用和挑战.
科学领域:
- 神经科学和计算生物学
- 医疗信息学医学信息学
- 公共卫生研究 公共卫生研究
背景情况:
- 神经和精神疾病对全球健康构成重大挑战.
- 复杂的多因素病因 (遗传,环境,社会经济) 复杂的诊断和治疗.
- 庞大而多样化的医学数据阻碍了用于研究和临床实践的信息提取.
研究的目的:
- 审查知识图 (KG) 在神经和精神疾病的最新应用.
- 讨论目前医疗KG的现状.
- 为了确定现有的障碍和局限性在现场.
主要方法:
- 关于将KG应用于神经和精神疾病的研究的文献综述.
- 对医疗知识现状和能力的分析图表.
- 确定挑战和未来的方向.
主要成果:
- 知识图,结合大数据和深度学习,显示了研究复杂大脑疾病的潜力.
- 医疗知识集 (KGs) 便于从大型,异构的医疗数据集中提取结构化信息.
- 审查强调了KG在这个领域的承诺和当前的局限性.
结论:
- 知识图是促进神经和精神疾病研究的宝贵工具.
- 克服当前的障碍对于充分发挥医疗KG的潜力至关重要.
- 需要进一步发展,以有效地将KG整合到临床和研究工作流程中.
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