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预防和个性化医疗的下一个前沿领域:人工智能驱动的解决方案。

The Next Frontiers in Preventive and Personalized Healthcare: Artificial Intelligent-Powered Solutions.

作者信息

Ardic Nurittin, Dinc Rasit

机构信息

Med-International UK Health Agency Ltd, Leicestershire, Great Britain (UK).

INVAMED Medical Innovation Institute, New York, United States.

出版信息

J Prev Med Public Health. 2025 May 29. doi: 10.3961/jpmph.25.080.

Abstract

Artificial intelligence (AI)-enabled technologies have the potential to significantly increase diagnostic accuracy, optimize treatment strategies, and improve patient outcomes. They are revolutionizing the field of preventive and personalized medicine by providing data-driven insights. AI is capable of analyzing large and complex datasets such as genomic, environmental, and lifestyle information much faster and more conveniently than traditional methods. Advanced algorithmic architectures in AI can predict disease risks, identify biomarkers, and tailor interventions to individual needs. The enabling role of AI in real-time monitoring, predictive analysis, and drug discovery demonstrates its transformative potential in healthcare. The role of AI in multi-omics integration, wearable technologies, and precision therapies promises to redefine global healthcare paradigms, making personalized medicine more accessible and effective. However, ethical concerns that need to be addressed to ensure fair and transparent implementation include data privacy, algorithmic bias, and regulatory gaps. This article examines the integration of AI technologies with personalized healthcare. The study also highlights the need for interdisciplinary collaboration to maximize the benefits of AI in preventive and personalized healthcare and overcome barriers.

摘要

人工智能(AI)技术有潜力显著提高诊断准确性、优化治疗策略并改善患者预后。它们通过提供数据驱动的见解,正在彻底改变预防医学和个性化医疗领域。与传统方法相比,人工智能能够更快、更便捷地分析大型复杂数据集,如基因组、环境和生活方式信息。人工智能中的先进算法架构可以预测疾病风险、识别生物标志物,并根据个人需求定制干预措施。人工智能在实时监测、预测分析和药物发现中的赋能作用彰显了其在医疗保健领域的变革潜力。人工智能在多组学整合、可穿戴技术和精准治疗中的作用有望重新定义全球医疗保健范式,使个性化医疗更易获得且更有效。然而,为确保公平透明实施而需要解决的伦理问题包括数据隐私、算法偏差和监管漏洞。本文探讨了人工智能技术与个性化医疗的整合。该研究还强调了跨学科合作的必要性,以最大化人工智能在预防和个性化医疗中的益处并克服障碍。

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