Journal of Preventive Medicine and Public Health

Review

The Next Frontiers in Preventive and Personalized Healthcare: Artificial Intelligent-powered Solutions: Rasit Dinc, Nurittin Ardic; J Prev Med Public Health. 2025;58(5):441-452. Published online May 29, 2025; DOI: https://doi.org/10.3961/jpmph.25.080

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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.

Summary

Key Message
Artificial intelligence significantly accelerates preventive and personalized medicine by analyzing complex genomic, environmental, and lifestyle datasets to predict disease risks, identify biomarkers, and tailor interventions to individual needs. Through real-time monitoring, predictive analysis, and precision therapies, AI-enabled technologies play a critical role in increasing diagnostic accuracy, optimizing treatment strategies, and improving patient outcomes. However, successful implementation requires addressing critical challenges such as data privacy concerns, algorithmic bias, regulatory gaps, and the need for interdisciplinary collaboration to provide equitable, transparent, and accessible AI-enabled healthcare solutions.

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Special Article

Introduction of Vaccinomics to Develop Personalized Vaccines in Light of Changes in the Usage of Hantaan Virus Vaccine (Hantavax^®) in Korea: Jong-Myon Bae; J Prev Med Public Health. 2019;52(5):277-280. Published online August 7, 2019; DOI: https://doi.org/10.3961/jpmph.19.018

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Abstract Summary PDF Supplementary Material

The Ministry of Food and Drug Safety of Korea made an official announcement in March 2018 that the total number of inoculations of Hantaan virus vaccine (Hantavax^®) would change from 3 to 4. Some aspects of this decision remain controversial. Based on the characteristics of Hantaan virus (HTNV) and its role in the pathogenesis of hemorrhagic fever with renal syndrome, it might be difficult to develop an effective and safe HTNV vaccine through the isolate-inactivate-inject paradigm. With the development of high-throughput ‘omics’ technologies in the 21st century, vaccinomics has been introduced. While the goal of vaccinomics is to develop equations to describe and predict the immune response, it could also serve as a tool for developing new vaccine candidates and individualized approaches to vaccinology. Thus, the possibility of applying the innovative field of vaccinomics to develop a more effective and safer HTNV vaccine should be considered.

Summary

Korean summary
신증후출혈열 (Hemorrhagic fever with renal syndrome, HFRS)를 예방하기 위한 백신들이 여러 가지로 개발 중에 있지만, 한탄 바이러스 (Hantaan virus) 의 병원체 특성과 HFRS의 임상적 특성으로 효과적이고 안전한 백신 개발을 어렵게 하고 있다. 투여할 백신에 대한 ‘면역과정을 이해하고 백신효능을 예측하여’ 백신개발에 활용하는 백신체학의 적용을 적극 강구할 필요가 있다.

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Association between predator species richness and human hantavirus infection emergence in Brazil
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