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Updated: Feb 7, 2026

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research

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数字双胞胎:大数据时代瘤学的新范式

L Mollica^1,2, C Leli^1,2, F Sottotetti¹

¹Medical Oncology Unit, Istituti Clinici Scientifici Maugeri IRCCS, Pavia, Italy.

ESMO real world data and digital oncology

|February 6, 2026

概括

数字双胞胎 (DTs) 创建医疗保健的虚拟模型,使用人工智能和现实世界的数据进行更好的临床预测. 虽然DT对癌症研究有希望,但在广泛临床使用之前,它面临着技术和道德上的障碍.

科学领域:

数字健康数字健康
人工智能在医学中的应用
计算生物学计算生物学

背景情况:

医疗数字化使大数据收集成为可能,需要人工智能用于预测工具.
数字双胞胎 (DTs) 提供"数字世界"来评估人工智能驱动的预测工具.
数字模型涉及数字模型和现实世界的对应物之间的双向交互.

研究的目的:

探索数字双胞胎 (DTs) 在增强临床决策预测工具方面的潜力.
研究各种数据源 (临床记录,多组学,患者结果) 的整合到虚拟模型中.
评估DTs在癌症研究和医疗保健教育中用于in silico模拟的实用性.

主要方法:

利用数字模拟的预测能力.
持续更新虚拟模型与现实生活数据.
将临床记录,多组数据和患者报告的结果整合到DTs.

主要成果:

诊断技术人员可以创建从临床前到临床研究适用的虚拟模型.
在癌症DT上的In silico模拟提供了对癌症生物学和临床实践的见解.
临床诊断技术有可能降低成本,克服传统研究的局限性 (例如,为罕见瘤招募患者).

结论:

数字双胞胎显示出在推进预测性医疗保健和研究方面具有重大潜力.
个人医疗技术为个性化医疗和改善医疗保健教育提供了一个有希望的方法.
目前,由于尚未解决的技术和道德挑战,DDT的广泛临床应用受到阻碍.

关键词:

人工智能的人工智能是人工智能.大数据就是大数据.癌症患者癌症患者临床瘤学临床瘤学数字双胞胎是一个数字双胞胎.

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