Affiliation:
1. Smt. Kashibai Navale College of Engineering, Pune, Maharashtra, India
Abstract
Depression is a serious mental illness that can be debilitating. It can interfere with daily activities and cause feelings of sadness, hopelessness, and despair. It is a mental health condition that can range in severity from mild to severe. The severity of depression can be assessed based on the number, intensity, and duration of symptoms, as well as their impact on an individual's daily functioning. Mild depression typically involves symptoms such as feeling sad, low energy, and a lack of motivation. These symptoms may not significantly interfere with an individual's ability to function in their daily life, and they may still be able to maintain their social and occupational obligations. Moderate depression involves more severe and persistent symptoms, such as a sense of hopelessness, persistent feelings of sadness, and difficulty concentrating or making decisions. These symptoms may make it challenging to fulfill daily responsibilities, and may result in social isolation or problems at work or school. Severe depression involves symptoms that significantly impair an individual's ability to function in their daily life, such as suicidal thoughts, complete loss of interest in activities, and difficulty with basic tasks such as personal hygiene or eating. Severe depression is a medical emergency and requires immediate professional intervention to prevent harm to oneself or others
Reference10 articles.
1. "Depression Detection using Convolutional Neural Networks and Transfer Learning", by V. Gupta, M. Mittal, and N. Parakh, in Proceedings of the 2020 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS).
2. "Detection of Depression from Twitter Data using Naive Bayes and Support Vector Machines", by A. Desai, S. Bhatia, and A. Patel, in Proceedings of the 2018 International Conference on Inventive Computation Technologies (ICICT).
3. "Depression Detection from Social Media Posts using Naive Bayes and Convolutional Neural Networks", by K. M. George and S. S. Kumar, in Proceedings of the 2019 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC).
4. "Depression Detection from Tweets using Machine Learning Techniques", by S. H. Lee, S. Lee, and S. S. Lee, in Proceedings of the 2019 IEEE International Conference on Artificial Intelligence and Information Systems (AIAIS).
5. "Depression Detection using Natural Language Processing and Machine Learning Techniques", by A. Yadav, A. Yadav, and N. Yadav, in Proceedings of the 2019 IEEE International Conference on Intelligent Computing and Control Systems (ICICCS).
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献