Investigation of Intelligent Methodologies in Prediction of Depression

Depression is one of the most common mental illnesses that can cause subsequently several health disorders among human population across the globe. The cause of depression or stress among individual might be different and it is highly challenge to predict the person who undergoes depression or stres...

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Bibliographic Details
Published in:	2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS) pp. 1188 - 1193
Main Authors:	Chintapalli, Meenakshi, Kanugula, Navya, Nagisetti, Laalithya, V, Abhishek Varma, S, Iwin Thanakumar Joseph, Bindu, G
Format:	Conference Proceeding
Language:	English
Published:	IEEE 02-02-2023
Subjects:	Adaptive systems Chatbot Deep learning Depression Human factors Learning (artificial intelligence) Machine Learning Machine learning algorithms Navigation Sociology Stress
Online Access:	Get full text
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Summary:	Depression is one of the most common mental illnesses that can cause subsequently several health disorders among human population across the globe. The cause of depression or stress among individual might be different and it is highly challenge to predict the person who undergoes depression or stress. It is analysed that 3.8% of entire human population (approximately 280 million and above) suffered due to depression that degrades their regular activities day by day. It is highly crucial to detect the depression at the earlier stage to save the life of the person failing which it leads to death too. Recently, deep learning and machine learning algorithms played a predominant role in efficient prediction, detection and recognition in various applications. This research article mainly focusses on investigation of various intelligent methodologies used for predicting depression among various peer groups, prime factors that leads to depression and also the measures to control depression effectively.
DOI:	10.1109/ICAIS56108.2023.10073713