自杀预测中的新兴主题和研究前沿:一个科学度分析
Kochumol Abraham1, Anish K R2, Greety Toms3
1Department of Computer Applications, Marian College Kuttikkanam, Peermade, IND.
Cureus
|July 12, 2024
概括
这项研究使用科学度分析来绘制自杀预测研究的地图,从1942年到2023年. 这些发现突显了自杀行为的复杂性和机器学习在加强自杀预防策略方面的潜力.
科学领域:
- 多学科研究包括医学,心理学和社会科学领域.
- 专注于全球卫生挑战和心理健康方面的进展.
背景情况:
- 自杀仍然是一个重要的全球健康问题.
- 尽管取得了进展,但有效的预测和预防策略仍是持续的挑战.
- 现有的研究往往侧重于特定的子主题或数据源.
研究的目的:
- 分析自杀预测研究的发展,模式和结果.
- 确定自杀预测的研究缺口和研究不足的领域.
- 提供自杀预测文献景观的全面映射.
主要方法:
- 使用Biblioshiny和VOSviewer进行科学度分析.
- 趋势分析,引用分析和关键词集群分析对1703篇文章 (1942-2023) 的分析.
- 检查出版趋势,地理分布和总体主题.
主要成果:
- 随着时间的推移,确定了自杀预测研究中的关键主题和趋势.
- 突出了自杀行为中生物,心理,社会和环境因素的复杂相互作用.
- 揭示了机器学习技术在自杀事件预测中的越来越大的影响.
结论:
- 科学度分析增强了对自杀预测的概念理解.
- 研究强调,自杀行为是多种相互作用因素的结果.
- 机器学习对改善自杀预防和干预工作具有重大潜力.
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