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              <text>Deep learning approaches to understanding psychological impacts on vulnerable populations</text>
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              <text>This chapter investigates the psychological effects on vulnerable groups, with a particular emphasis on the relationship between deep learning techniques and the impact of climate. Vulnerable groups confront particular problems, which might lead to negative psychological results. Investigating this complexity is critical to designing effective intervention techniques. Using sophisticated deep learning techniques, this study seeks to find subtle patterns and correlations in a variety of datasets, including psychological markers, socioeconomic characteristics, and climatic variables. The work employs a comprehensive technique that includes deep learning models, feature extraction, and interpretability analysis to untangle complicated relationships. Preliminary findings imply that deep learning approaches might uncover previously unknown links between climate change and psychological effects on vulnerable groups. This insight adds to a more comprehensive understanding of the difficulties. This understanding contributes to a more holistic grasp of the challenges faced by these groups. By including climate-related factors into the deep learning framework, this study hopes to close the gap between environmental impacts and psychological  2024, IGI Global. All rights reserved.</text>
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              <text>Mehta M.; Prasad R.S.; Giri M.; Rajendran R.K.</text>
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              <text>The Climate Change Crisis and Its Impact on Mental Health, pp. 159-168.</text>
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              <text>&lt;a href="https://doi.org/10.4018/979-8-3693-3272-6.ch012" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.4018/979-8-3693-3272-6.ch012&lt;/a&gt;
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              <text>ISBN: 979-836933273-3; 979-836933272-6</text>
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              <text>Mehta M., Christ University, India; Prasad R.S., Christ University, India; Giri M., Christ University, India; Rajendran R.K., Christ University, India</text>
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