Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

A Novel Approach for Detecting Schizophrenia using Deep Learning Techniques like LSTM and CNN from Social Media

Author : N Sandeep Chaitanya 1 Ch Sai Sri Harsha 2 P Srikanth 3 T Prashanth 4 L Nikhitha 5

Date of Publication :1st June 2023

Abstract: Schizophrenia is a serious intellectual disease that is one of the main reasons for disability in the world. The detection of this kind of a mental disorder is paramount for the well being of human beings; Schizophrenia gets usually identified in later stages, where it becomes a lot difficult for the person to get treated hence we need another way to identify schizophrenia beforehand so that it will not go out of control and can be treated smoothly. One of the ways currently to detect schizophrenia is using MRI scans of the brain which can only detect schizophrenia in later stages. The world we live in is a digital world and almost all of the people including all age groups use the internet and use social media as a platform to express their opinions and feelings. Thus by using the social media profile of a person we would be able to detect Schizophrenia. This paper mainly deals with various existing methodologies and drawbacks related to the above problems like detecting Schizophrenia in early stages and detection of Schizophrenia through different types of social media posts.

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