The most frequent psychiatric disorders are depression and post-traumatic stress disorder. Machine learning algorithms are effective tools for predicting psychiatric diseases. The extent to which society is not widely known, most of the time disguised, many more victims does not mention in a public health concern is child abuse and neglect. This Project is mainly focused to rehabilitate the Child, Abuse show various methods is bodily, mind, and several abuse, as well as domestic violence. A child who is subjected to any of the aforementioned sorts of abuse is at danger of being isolated, developing anxiety, depression, and mental trauma, as well as having difficulty learning and building social relationships. Anxiety and depression in children are frequently misdiagnosed. In this study, we used the LSTM algorithm to create a Child Abuse Depression Detection and Recommendation Model that can recognise signals of anxiety and depression in young children’s symptoms. On Child Abuse Depression Symptom instances in India, the proposed Deep-LSTM ensemble model is assessed using several forms.
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18 August 2023
GREEN COMPUTING FOR COMMUNICATION TECHNOLOGIES
25–26 February 2022
Salem, India
Research Article|
August 18 2023
Depression and post traumatic stress disorder prediction using machine learning
Nisha Thambidurai;
Nisha Thambidurai
a)
Department of Information Technology, Sona College of Technology
, Salem, Tamil Nadu, India
a)Corresponding Author: [email protected]
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Vasanthi Sumdramoorthy;
Vasanthi Sumdramoorthy
b)
Department of Information Technology, Sona College of Technology
, Salem, Tamil Nadu, India
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Sivanandhini Ganapathi;
Sivanandhini Ganapathi
c)
Department of Information Technology, Sona College of Technology
, Salem, Tamil Nadu, India
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Srija Suresh
Srija Suresh
d)
Department of Information Technology, Sona College of Technology
, Salem, Tamil Nadu, India
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a)Corresponding Author: [email protected]
AIP Conf. Proc. 2857, 020044 (2023)
Citation
Nisha Thambidurai, Vasanthi Sumdramoorthy, Sivanandhini Ganapathi, Srija Suresh; Depression and post traumatic stress disorder prediction using machine learning. AIP Conf. Proc. 18 August 2023; 2857 (1): 020044. https://doi.org/10.1063/5.0165190
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