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@article{180462,
        author = {Pradeep.M and S.Chitra Nayagam},
        title = {DEPRESSION AND ITS MITIGATION TECHNIQUE USING  MACHINE LEARNING APPROACHES},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {2417-2423},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180462},
        abstract = {Depression represents the most common mental health disorder, affecting millions of people worldwide. The symptoms partially overlap with those of bipolar disorder, schizophrenia, and even Parkinson’s disease. Untreated depression might lead to serious health complications. Traditionally, diagnosis has been challenging and somewhat subjective because it relies on the doctor’s experience. Researchers have begun coupling increasingly diverse data modalities with machine learning techniques in the hope of raising the resulting depression diagnosis accuracy. Depression is getting more and more prevalent due to factors associated with the modern lifestyle, including peer pressure, work culture, stress, emotional imbalances, family issues, and social anxiety. This disorder significantly interferes with daily functioning; in more severe forms, it is associated with suicidal thoughts and such feelings as sadness, anxiety, and apathy. The purpose of this work is to compare the predictive power of many machine learning algorithms for depression by evaluating them on different parameters.},
        keywords = {Machine learning, depression, mental health challenges, suicidal thoughts, emotional struggles, modern life pressures.},
        month = {June},
        }