癌症护理中的人工智能:在新出现的挑战和未来的机会中,彻底改变了诊断,治疗和精准医学
Chandrabose Selvaraj1, William C Cho2, Kulanthaivel Langeswaran3
1CSRDD Lab, Bioinformatics Division, Department of Marine Biotechnology, AMET University (Deemed to Be University), East Coast Road, Kanathur, Chennai, Tamil Nadu 603112 India.
3 Biotech
|September 22, 2025
概括
人工智能 (AI) 增强了从检测到药物发现的癌症护理. 虽然人工智能显示出前景,但临床整合必须解决数据质量,验证和解释性方面的挑战.
科学领域:
- 在瘤学瘤学.
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 人工智能 (AI) 正在迅速推进癌症治疗,影响早期检测,诊断,预后,治疗计划和药物发现等领域.
- 对人工智能在瘤学中的当前作用和局限性的全面理解对于未来的研究和临床转化至关重要.
研究的目的:
- 系统地审查和综合人工智能应用在癌症护理连续性的证据.
- 确定关键的研究集群,方法的优缺点,以及未来的研究方向,用于AI在瘤学.
主要方法:
- 在PubMed,Scopus,Web of Science和IEEE Xplore (2013年1月至2024年12月) 进行了系统的文献搜索,遵循PRISMA指南.
- 在人类或人类衍生的癌症数据集中包含使用人工智能的同行评审原始研究研究.
- 数据提取和偏差风险评估由两位评论员独立进行,其中包括来自4852个记录的120项研究.
主要成果:
- 人工智能应用被分为五个集群:成像/放射学,基因组学/生物标志物发现,药物发现/再利用,临床决策支持和患者监测.
- 卷积神经网络主导着成像任务,而机器学习分类器在基因组学中普遍存在.
- 大多数研究表明,与传统方法相比,性能优越,但缺乏多中心验证,突出了数据异质性,可解释性和整合挑战等问题.
结论:
- 人工智能为改善癌症治疗提供了巨大的潜力.
- 必须克服包括数据质量,验证,可解释性和实际翻译在内的关键挑战.
- 跨学科合作,标准化报告和大规模验证研究对于在临床瘤学中推进人工智能至关重要.
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