Scholarlink

Machine learning (ML) has displayed satisfactory results in improving the treatment and diagnosis of mental health in adults. A systematic review has been carried out in this study to find out the effectiveness of ML in treating and diagnosing mental health conditions across different populations. Seven studies were identified for inclusion based on two-phase screening process. It has been observed that there are differences in ML effectiveness across various mental health conditions. The methods adopted in the selected studies highlight the complexity of ML applications in mental health conditions. An important discovery was made regarding data types and ML algorithms employed. Overall, this study highlights the capability of ML in treating mental health, while also stressing the need for more research and testing.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

MindEase: Systematic Review for Unravelling Mental Health with Machine Learning Approach in Adults

  • 章节

  • 发表日期：

    2025年

查看全文
  • Gypsy Nandi,
  • Lal Omega Boro

摘要

Machine learning (ML) has displayed satisfactory results in improving the treatment and diagnosis of mental health in adults. A systematic review has been carried out in this study to find out the effectiveness of ML in treating and diagnosing mental health conditions across different populations. Seven studies were identified for inclusion based on two-phase screening process. It has been observed that there are differences in ML effectiveness across various mental health conditions. The methods adopted in the selected studies highlight the complexity of ML applications in mental health conditions. An important discovery was made regarding data types and ML algorithms employed. Overall, this study highlights the capability of ML in treating mental health, while also stressing the need for more research and testing.