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公共卫生领域的人工智能:连接当今趋势与未来可能性

Artificial Intelligence in Public Health: Bridging Today's Trends with Tomorrow's Possibilities.

作者信息

Giansanti Daniele, Costantini Giovanni

机构信息

Centre Tisp, Istituto Superiore Di Sanita, 000161 Rome, Italy.

Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.

出版信息

Bioengineering (Basel). 2025 May 23;12(6):559. doi: 10.3390/bioengineering12060559.

DOI:10.3390/bioengineering12060559
PMID:40564376
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12189652/
Abstract

Driven by the unprecedented challenges of the COVID-19 pandemic, the healthcare sector has witnessed remarkable-and at times sometimes overwhelming-advancements in the role of artificial intelligence (AI) [...].

摘要

在新冠疫情带来的前所未有的挑战推动下,医疗保健行业见证了人工智能(AI)作用取得的显著进步,有时甚至是压倒性的进步[……]

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46c4/12189652/e6e51c96fb47/bioengineering-12-00559-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46c4/12189652/e6e51c96fb47/bioengineering-12-00559-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46c4/12189652/e6e51c96fb47/bioengineering-12-00559-g001.jpg

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本文引用的文献

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The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development.人工智能在大流行应对中的作用:从流行病学建模到疫苗研发。
Mol Biomed. 2025 Jan 3;6(1):1. doi: 10.1186/s43556-024-00238-3.
2
AI in Cytopathology: A Narrative Umbrella Review on Innovations, Challenges, and Future Directions.细胞病理学中的人工智能:关于创新、挑战及未来方向的叙述性综合综述
J Clin Med. 2024 Nov 9;13(22):6745. doi: 10.3390/jcm13226745.
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Advancing Indoor Epidemiological Surveillance: Integrating Real-Time Object Detection and Spatial Analysis for Precise Contact Rate Analysis and Enhanced Public Health Strategies.
推进室内流行病学监测:实时目标检测与空间分析的整合,用于精确接触率分析和增强公共卫生策略。
Int J Environ Res Public Health. 2024 Nov 13;21(11):1502. doi: 10.3390/ijerph21111502.
4
Exploring Factors Influencing Patient Delay Behavior in Oral Cancer: The Development of a Risk Prediction Model in Western China.探索影响口腔癌患者延迟行为的因素:中国西部风险预测模型的构建
Healthcare (Basel). 2024 Nov 12;12(22):2252. doi: 10.3390/healthcare12222252.
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Prospective and External Validation of Machine Learning Models for Short- and Long-Term Mortality in Acutely Admitted Patients Using Blood Tests.使用血液检测对急性入院患者短期和长期死亡率的机器学习模型进行前瞻性和外部验证。
J Clin Med. 2024 Oct 27;13(21):6437. doi: 10.3390/jcm13216437.
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J Clin Med. 2024 Oct 16;13(20):6172. doi: 10.3390/jcm13206172.
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