Suppr超能文献

人工智能驱动的精准医学:利用遗传风险因素优化彻底改变医疗保健。

AI-powered precision medicine: utilizing genetic risk factor optimization to revolutionize healthcare.

作者信息

Alsaedi Sakhaa, Ogasawara Michihiro, Alarawi Mohammed, Gao Xin, Gojobori Takashi

机构信息

Computer Science, Division of Computer, Electrical and Mathematical Sciences and Engineering (CEMSE), King Abdullah University of Science and Technology (KAUST), 23955-6900 Thuwal, Kingdom of Saudi Arabia.

Center of Excellence on Smart Health, King Abdullah University of Science and Technology (KAUST), 23955-6900 Thuwal, Kingdom of Saudi Arabia.

出版信息

NAR Genom Bioinform. 2025 May 5;7(2):lqaf038. doi: 10.1093/nargab/lqaf038. eCollection 2025 Jun.

Abstract

The convergence of artificial intelligence (AI) and biomedical data is transforming precision medicine by enabling the use of genetic risk factors (GRFs) for customized healthcare services based on individual needs. Although GRFs play an essential role in disease susceptibility, progression, and therapeutic outcomes, a gap exists in exploring their contribution to AI-powered precision medicine. This paper addresses this need by investigating the significance and potential of utilizing GRFs with AI in the medical field. We examine their applications, particularly emphasizing their impact on disease prediction, treatment personalization, and overall healthcare improvement. This review explores the application of AI algorithms to optimize the use of GRFs, aiming to advance precision medicine in disease screening, patient stratification, drug discovery, and understanding disease mechanisms. Through a variety of case studies and examples, we demonstrate the potential of incorporating GRFs facilitated by AI into medical practice, resulting in more precise diagnoses, targeted therapies, and improved patient outcomes. This review underscores the potential of GRFs, empowered by AI, to enhance precision medicine by improving diagnostic accuracy, treatment precision, and individualized healthcare solutions.

摘要

人工智能(AI)与生物医学数据的融合正在改变精准医学,通过基于个体需求利用遗传风险因素(GRF)提供定制化医疗服务。尽管GRF在疾病易感性、进展和治疗结果中起着至关重要的作用,但在探索它们对人工智能驱动的精准医学的贡献方面仍存在差距。本文通过研究在医学领域将GRF与AI结合使用的意义和潜力来满足这一需求。我们研究它们的应用,特别强调它们对疾病预测、治疗个性化和整体医疗改善的影响。本综述探讨了AI算法在优化GRF使用方面的应用,旨在推动疾病筛查、患者分层、药物发现和疾病机制理解等方面的精准医学发展。通过各种案例研究和实例,我们展示了将由AI推动的GRF纳入医学实践的潜力,从而实现更精确的诊断、靶向治疗和改善患者预后。本综述强调了在AI赋能下,GRF通过提高诊断准确性、治疗精准度和个性化医疗解决方案来增强精准医学的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a798/12051108/6be1a2cc18c4/lqaf038fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验