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In this modern world, everything is developing rapidly in terms of technologies, inventions, etc. With this, people’s lifestyles have also changed a lot. With all these things, one thing that most people neglect is their health. There are many reasons for neglecting it like some people don’t feel it is important, financial issues, and many more. One of the most dangerous issues related to health is mental health disorders. This issue is very harmful for a person that if not treated well can take the life of an individual. In our research, our main objective is to use data like behavioral data can create a machine learning (ML) model that will help to predict different health disorders related to mental health, which are depression, anxiety, and stress. By applying different ML algorithms, we came to the result almost every algorithm can predict mental health issues accurately. We calculated the performance measure using accuracy, precision, recall, and F1-score. Among all the algorithms, Gradient Boosting (GB) and Gradient Boosting with Decision Tree (DT) gave the highest accuracy.

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Enhancing Mental Disorder Prediction Using Machine Learning and Boosting Algorithms

  • 会议论文

  • 发表日期：

    2026年

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  • Rasmita Gantayet,
  • Sibo Prasad Patro,
  • Neelamadhab Padhy

摘要

In this modern world, everything is developing rapidly in terms of technologies, inventions, etc. With this, people’s lifestyles have also changed a lot. With all these things, one thing that most people neglect is their health. There are many reasons for neglecting it like some people don’t feel it is important, financial issues, and many more. One of the most dangerous issues related to health is mental health disorders. This issue is very harmful for a person that if not treated well can take the life of an individual. In our research, our main objective is to use data like behavioral data can create a machine learning (ML) model that will help to predict different health disorders related to mental health, which are depression, anxiety, and stress. By applying different ML algorithms, we came to the result almost every algorithm can predict mental health issues accurately. We calculated the performance measure using accuracy, precision, recall, and F1-score. Among all the algorithms, Gradient Boosting (GB) and Gradient Boosting with Decision Tree (DT) gave the highest accuracy.