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人工智能不会给我们精准医学

Lorenzo Farina¹

¹Dipartimento di Ingegneria Informatica Automatica e Gestionale, Sapienza Università di Roma, Rome, Italy.

Annali dell'Istituto superiore di sanita

|June 26, 2024

概括

人工神经网络,在精准医学中很受欢迎,不是生物. 将临床专业知识与数据分析相结合,对于了解患者独特特征至关重要.

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
基因组学就是基因组学.

背景情况:

人类DNA测序有望带来医学革命,但由于基因型-表型复杂性而面临限制.
精准医学利用分子和临床"omics"数据进行量身定制的治疗.
庞大而异质的数据集需要先进的计算分析.

研究的目的:

批判性地评估人工神经网络在精准医学中的生物相关性.
倡导一种综合方法,将计算分析与临床专业知识相结合.

主要方法:

分析人工神经网络 (ANN) 原则及其在生物信息学中的应用.
对精准医学数据分析当前实践的审查.
整合数据驱动和专业知识驱动方法的概念框架.

主要成果:

人工神经网络缺乏直接的生物基础,尽管声称模拟人类大脑.
目前的计算方法本身不足以分析复杂的患者数据.
精准医学的有效性依赖于计算分析和临床洞察力的桥梁.

结论:

人工神经网络是数学工具,而不是生物模型,在精准医学的背景下.
有效的精准医学需要数据科学家和临床医生之间的协同合作.
了解个体患者的独特性至关重要,需要将不同类型的数据与专家知识整合起来.

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