分析糖尿病检测和分类:一个图书识别综述 (2000-2023)
Jannatul Ferdaus1, Esmay Azam Rochy1, Uzzal Biswas1
1Electronics and Communication Engineering Discipline, Khulna University, Khulna 9208, Bangladesh.
Sensors (Basel, Switzerland)
|August 29, 2024
概括
这份对2000-2023年糖尿病检测和分类研究的文献计量分析揭示了领先的国家和机器学习和深度学习等趋势关键词.
科学领域:
- * 医学信息学 医学信息学
- * 计算生物学 * 计算生物学
- * * 公共卫生 公共卫生
背景情况:
- * 糖尿病仍然是一个全球性的健康挑战,需要先进的检测和分类方法.
- * 在过去的20年里,该领域的学术研究显著扩大.
- * 了解研究趋势和贡献对于未来的进展至关重要.
研究的目的:
- *对有关糖尿病检测和分类的学术研究进行文献分析.
- *从2000年到2023年确定关键趋势,有影响力的国家和普遍的研究主题.
- *绘制科学格局的地图,并评估该领域研究的影响.
主要方法:
- * 使用科学网络数据库进行图书统计分析.
- *遵守PRISMA 2020研究选择框架.
- *在863个选定的出版物中应用绩效分析和科学绘图技术.
主要成果:
- *印度,中国和美国在与糖尿病检测和分类相关的出版物和引用方面处于领先地位.
- *机器学习,糖尿病视网膜病变和深度学习是最常见的关键词.
- *主要的研究主题包括糖尿病的分类,诊断和验证.
结论:
- * 该研究提供了关于糖尿病检测和分类的学术研究的全面概述.
- *确定了糖尿病研究中的全球主要参与者和新兴技术趋势.
- *研究结果为研究人员,政策制定者和医疗保健专业人员提供了有价值的见解.
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