癌症中的全息图学和人工智能研究与应用。

IF 3.3 3区 医学 Q2 ENGINEERING, BIOMEDICAL
Ye Zhang, Wenwen Ma, Zhiqiang Huang, Kun Liu, Zhaoyi Feng, Lei Zhang, Dezhi Li, Tianlu Mo, Qing Liu
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引用次数: 0

摘要

癌症的发病率和致死率都很高,是人类健康的重大威胁。随着高通量技术的发展,已经积累了不同类型的癌症基因组学数据,包括基因组学、表观基因组学、转录组学、蛋白质组学和代谢组学。要了解肿瘤发生发展的内在机制,需要对各种 omics 数据进行综合分析。然而,整合如此海量的数据是当今面临的主要挑战之一。机器学习等人工智能技术正在成为分析和理解疾病多组学数据的实用工具。这极大地优化了癌症筛查、诊断和治疗的现有研究范式。此外,随着医疗信息化的发展,智能医疗也受到了广泛关注。作为创新医疗的重要组成部分,对癌症患者进行实用的智能预后分析和个性化治疗也十分必要。本文介绍了近年来先进的多组学数据分析技术,介绍了omics数据与人工智能结合应用于肿瘤疾病的案例和优势,最后简要阐述了现阶段多组学分析和人工智能面临的挑战,旨在为肿瘤学研究提供新的视角,为肿瘤的个性化治疗提供可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research and application of omics and artificial intelligence in cancer.

Cancer has a high incidence and lethality rate, which is a significant threat to human health. With the development of high-throughput technologies, different types of cancer genomics data have been accumulated, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics. A comprehensive analysis of various omics data is needed to understand the underlying mechanisms of tumor development. However, integrating such a massive amount of data is one of the main challenges today. Artificial intelligence (AI) techniques such as machine learning are now becoming practical tools for analyzing and understanding multi-omics data on diseases. Enabling great optimization of existing research paradigms for cancer screening, diagnosis, and treatment. In addition, intelligent healthcare has received widespread attention with the development of healthcare informatization. As an essential part of innovative healthcare, practical, intelligent prognosis analysis and personalized treatment for cancer patients are also necessary. This paper introduces the advanced multi-omics data analysis technology in recent years, presents the cases and advantages of the combination of both omics data and AI applied to cancer diseases, and finally briefly describes the challenges faced by multi-omics analysis and AI at the current stage, aiming to provide new perspectives for oncology research and the possibility of personalized cancer treatment.

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来源期刊
Physics in medicine and biology
Physics in medicine and biology 医学-工程:生物医学
CiteScore
6.50
自引率
14.30%
发文量
409
审稿时长
2 months
期刊介绍: The development and application of theoretical, computational and experimental physics to medicine, physiology and biology. Topics covered are: therapy physics (including ionizing and non-ionizing radiation); biomedical imaging (e.g. x-ray, magnetic resonance, ultrasound, optical and nuclear imaging); image-guided interventions; image reconstruction and analysis (including kinetic modelling); artificial intelligence in biomedical physics and analysis; nanoparticles in imaging and therapy; radiobiology; radiation protection and patient dose monitoring; radiation dosimetry
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