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本文引用的文献

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Inclusion of nonrandomized studies of interventions in systematic reviews of interventions: updated guidance from the Agency for Health Care Research and Quality Effective Health Care program.干预措施系统评价中纳入非随机研究:卫生保健研究和质量有效医疗保健项目机构的最新指南。
J Clin Epidemiol. 2022 Dec;152:300-306. doi: 10.1016/j.jclinepi.2022.08.015. Epub 2022 Sep 19.
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Digital healthcare: the future.数字医疗:未来
Future Healthc J. 2022 Jul;9(2):113-117. doi: 10.7861/fhj.2022-0046.
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Ethical Issues of Artificial Intelligence in Medicine and Healthcare.医学与医疗保健领域中人工智能的伦理问题。
Iran J Public Health. 2021 Nov;50(11):i-v. doi: 10.18502/ijph.v50i11.7600.
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Cohort Studies.队列研究。
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5
Trends of global health literacy research (1995-2020): Analysis of mapping knowledge domains based on citation data mining.全球健康素养研究趋势(1995-2020):基于引文数据挖掘的知识领域图谱分析。
PLoS One. 2021 Aug 9;16(8):e0254988. doi: 10.1371/journal.pone.0254988. eCollection 2021.
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A scoping review of cohort studies assessing traditional Chinese medicine interventions.评估中医药干预措施的队列研究的范围综述。
BMC Complement Med Ther. 2020 Nov 23;20(1):361. doi: 10.1186/s12906-020-03150-9.
7
Telehealth Benefits and Barriers.远程医疗的益处与障碍。
J Nurse Pract. 2021 Feb;17(2):218-221. doi: 10.1016/j.nurpra.2020.09.013. Epub 2020 Oct 21.
8
Population-Based Birth Cohort Studies in Epidemiology.基于人群的出生队列研究在流行病学中的应用。
Int J Environ Res Public Health. 2020 Jul 23;17(15):5276. doi: 10.3390/ijerph17155276.
9
Data Analytics and Applications of the Wearable Sensors in Healthcare: An Overview.可穿戴传感器在医疗保健中的数据分析和应用:概述。
Sensors (Basel). 2020 Mar 3;20(5):1379. doi: 10.3390/s20051379.
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下一代队列研究即将到来的变革。

Oncoming Revolution in the Next Generation of Cohort Studies.

作者信息

Moameri Hossein, Norouzi Mojtaba, Haghdoost Ali Akbar, Golkar Mostafa Hosseini

机构信息

Department of Biostatistics and Epidemiology, Faculty of Public Health, Kerman University of Medical Sciences, Kerman, Iran.

HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.

出版信息

Iran J Public Health. 2024 Nov;53(11):2595-2599. doi: 10.18502/ijph.v53i11.16963.

DOI:10.18502/ijph.v53i11.16963
PMID:39619915
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11607157/
Abstract

The world is changing rapidly, mainly due to the impact of megatrends that have an impact on the entire human life, particularly in medical sciences. Medical research methodologies such as cohort studies provide very critical information, but it is not clear what would be its destination in the future. In this short article, we have tried to offer a somewhat different perspective on the future of cohort studies by analyzing the texts and their conclusions from the author's viewpoint. According to our assessment, cohorts will play a key role in medical research, but their methodology will significantly change in terms of designing, implementing, analysing, and applying the findings. The new generation of cohort study extracts most of their information from electronic health records, and it is not just restricted to a particular geographic area. With the changes in the levels of occupational exposure, risk factors, and the introduction of Omics, likely, occupational and birth cohorts as well as human diseases will likely undergo fundamental changes in the future. Big data will provide researchers with new opportunities, but information extraction and analysis require a team of specialists from several scientific fields. Furthermore, participants are likely to play a more active role in setting priorities and implementing research findings.

摘要

世界正在迅速变化,这主要是由于一些大趋势的影响,这些趋势对整个人类生活产生影响,尤其是在医学领域。队列研究等医学研究方法提供了非常关键的信息,但尚不清楚其未来的发展方向。在这篇短文中,我们试图从作者的观点分析相关文本及其结论,从而对队列研究的未来提供一个略有不同的视角。根据我们的评估,队列将在医学研究中发挥关键作用,但其方法在设计、实施、分析和应用研究结果方面将发生显著变化。新一代队列研究大部分信息来自电子健康记录,并且不仅限于特定地理区域。随着职业暴露水平、风险因素的变化以及组学的引入,职业队列、出生队列以及人类疾病未来可能会发生根本性变化。大数据将为研究人员提供新的机会,但信息提取和分析需要来自多个科学领域的专家团队。此外,参与者在确定优先事项和实施研究结果方面可能会发挥更积极的作用。