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            <name>Title</name>
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                <text>Faculty Publications</text>
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    <name>Conference Paper</name>
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          <name>Creator</name>
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              <text>Sailaja, Petikam; Palaparthy, Hakalyah; Rajeswari, B.; Rao, Peketi Kasi Visweswara Sita Rama; Prema, D.; Ajay Sundar, M.</text>
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          <name>Title</name>
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              <text>A Study on the Ethics of using Artificial Intelligence in Mental Health Treatment and its Legality</text>
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          <name>Date</name>
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              <text>01-01-2025</text>
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              <text>Proceedings of the 2025 1st International Conference on Advances in Engineering and Computing Technologies for Sustainable Development, AECTSD 2025;</text>
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              <text>&lt;a href="https://doi.org/10.1109/AECTSD65988.2025.11410624" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/AECTSD65988.2025.11410624&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105036512854?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105036512854?origin=resultslist&lt;/a&gt;</text>
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              <text>Sailaja P., Saveetha Institute Of Medical And Technical Sciences, Saveetha School Of Law, Chennai, India; Palaparthy H., Affiliated To Telangana University, Mjptbcwr Degree College, Department Of Psychology, Nizamabad, India; Rajeswari B., Dhana Lakshmi Srinivasan University, School Of Law, Trichy, India; Rao P.K.V.S.R., Christ University, School Of Law, Bangalore, India; Prema D., Saveetha Institute Of Medical And Technical Sciences, Saveetha School Of Law, Chennai, India; Ajay Sundar M., Affiliated To The Tamil Nadu Ambedkar Law University, S. Thangapazhalm Law College, Chennai, India</text>
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              <text>The development of artificial intelligence (AI) has transformed mental health care through offering new and feasible solutions to old assumptions. The moral concerns related to the use of AI in the mental health, however, could not be overlooked. A thorough grasp of how AI can be used throughout the patient journey is essential to advancing AI technology in the realm of mental health and overcoming its present restrictions. To reduce it to three columns, or one dataset, five Facebook datasets were gathered from Kaggle. The preprocessing procedure enhances the dataset's quality by using user tweets. Four datasets about depression were taken from the Kaggle website. After the preprocessing is finished, we will refine four pre-trained BERT models using the Hugging Face package. We will be able to create a predictive model for identifying depression with this method. The effectiveness of our refined BERT models for depression identification was assessed using a number of metrics. Our healthcare system could be greatly enhanced by AI, but we can only realise this potential if we begin addressing the moral and legal issues that currently confront us.  2025 IEEE.</text>
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          <name>Subject</name>
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              <text>Artificial intelligence; BERT models; legality; mental health</text>
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          <name>Publisher</name>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>ISBN: 979-833158156-5;</text>
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              <text>English</text>
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              <text>Restricted Access; Hardcopy may be available in the library</text>
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              <text>online</text>
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