Understanding the Levels of Evidence in Medical Research.

Arvind Vatkar, Sachin Kale, Ashok Shyam, Sushant Srivastava
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引用次数: 0

Abstract

The advancement of evidence-based medicine (EBM) depends on the evidence hierarchy, a framework for classifying research approaches according to their dependability and quality. It dates back to the middle of the 20th century and classifies techniques such as expert opinions, case reports, randomized controlled trials, and systematic reviews. However, problems such as prejudice and moral constraints still exist. Evidence paradigms are being redefined by emerging technologies such as artificial intelligence, big data, and real-world data. This calls for dynamic hierarchies that include many forms of evidence. High-quality data are essential for developing flexible frameworks for contemporary medicine and influencing clinical guidelines, public health regulations, and educational initiatives.

理解医学研究中的证据水平。
循证医学(EBM)的进步依赖于证据层次,证据层次是一种根据研究方法的可靠性和质量对其进行分类的框架。它可以追溯到20世纪中叶,对专家意见、病例报告、随机对照试验和系统评价等技术进行分类。然而,偏见和道德约束等问题仍然存在。人工智能、大数据和现实世界数据等新兴技术正在重新定义证据范式。这就需要包含多种形式证据的动态层次结构。高质量数据对于制定当代医学的灵活框架和影响临床指南、公共卫生法规和教育举措至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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128
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30 weeks
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