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基于单细胞检测的临床转化新模式——临床人工智能单细胞OACSTPCD

Clinical and translational mode of single-cell measurements:clinical artificial intelligent single-cell

中文摘要英文摘要

随着单细胞检测技术的迅速发展和成熟,单细胞生物学和病理学已成为了解疾病的新兴学科.然而,解决临床医生提出的关于如何将单细胞检测应用于临床实践、将单细胞系统生物学的信号转化为明确的临床表型、并预测患者对治疗反应的问题至关重要.本文提出了一个称为"临床人工智能单细胞"(clinical artificial intelligent single-cell,caiSC)的新系统,具有临床单细胞信息学的动态生成、人工智能分析、分子多模态参考模块储存、临床信息输入输出,以及基于人工智能计算程序化的能力.该系统在单细胞水平上为临床诊断、监测和疾病预测提供可靠且快捷的信息.临床人工智能单细胞是将单细胞检测转化为临床应用、助力临床医生决策、改善医疗服务质量的重要里程碑.鉴于与临床人工智能单细胞相关生物技术的快速发展,越来越多的证据支持"临床人工智能单细胞假说"实现的可能性.因此,我们呼吁广大科学家和临床医生加大对临床人工智能单细胞的关注和研究,相信临床人工智能单细胞将为临床分子医学的未来带来曙光.

With rapid development and maturity of single-cell measurements,single-cell biology and pathology has become an emerging discipline to understand the disease.However,it is important to address concerns raised by clinicians as to how to apply single-cell measurements for clinical practice,translate the signals of single-cell systems biology into determination of clinical phenotype,and predict patient response to therapies.This paper proposes a new system coined as the clinical artificial intelligent single-cell(caiSC)with the dynamic generator of clinical single-cell informatics,artificial intelligent analyzers,molecular multimodal reference boxes,clinical inputs and outputs,and AI-based computerization.This system provides reliable and rapid information for impacting clinical diagnoses,monitoring,and prediction of the disease at the single-cell level.The caiSC represents an important step and milestone to translate the single-cell measurement into clinical application,assist clinicians'decision-making,and improve the quality of medical services.There is increasing evidence to support the possibility of the caiSC proposal,since the corresponding biotechnologies associated with caiSCs are rapidly developed.Therefore,we call the special attention and efforts from various scientists and clinicians on the caiSCs and believe that the appearance of the caiSCs can shed light on the future of clinical molecular medicine.

王向东;Charles A.Powell;马勤;樊嘉

上海市临床生物信息学研究所,上海 200030,中国||复旦大学临床生物信息学中心,上海 200030,中国||复旦大学附属中山医院呼吸科,上海 200032,中国西奈山伊坎医学院肺部、重症监护和睡眠医学科,纽约,美国俄亥俄州立大学医学院生物医学信息系计算生物学与生物信息学部,纽约,美国复旦大学附属中山医院肝肿瘤外科,上海 200032,中国||复旦大学肝癌研究所,复旦大学生物医学研究院,癌变与侵袭原理教育部重点实验室,上海 200030,中国

基础医学

人工智能基因测序医疗多组学单细胞生物学临床人工智能单细胞

artificial intelligencegene sequencingmedicinemulti-omicssingle-cell biologyclinical artificial intelligent single-cell

《中国临床医学》 2024 (005)

691-695 / 5

10.12025/j.issn.1008-6358.2024.20241086

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