Smart Self-Immolation Prediction Techniques: An Analytical Study for Predicting Suicidal Tendencies Using Machine Learning Algorithms-Reference-Cited by-同舟云学术

Smart Self-Immolation Prediction Techniques: An Analytical Study for Predicting Suicidal Tendencies Using Machine Learning Algorithms

Published:2021-07-16 Issue: Volume: Page:69-91
ISSN:2522-8595
Container-title:Smart IoT for Research and Industry
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Author:

Chanda Kaushik,Ghosh Ahona,Dey Sharmistha,Bose Rajesh,Roy Sandip

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-71485-7_4

Reference63 articles.

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3. Kamalja, K. K., & Khangar, N. V. (2017). A statistical study of suicidal behaviour of Indians. Egyptian Journal of Forensic Sciences, 7(1), 12.

4. Ramalingam, D., Sharma, V., & Zar, P. (2019). Study of depression analysis using machine learning techniques. International Journal of Innovative Technology and Exploring Engineering, 8(7C2), 187–191.

5. Liu, X., Liu, X., Sun, J., Yu, N. X., Sun, B., Li, Q., & Zhu, T. (2019). Proactive Suicide Prevention Online (PSPO): Machine identification and crisis management for Chinese social media users with suicidal thoughts and behaviours. Journal of Medical Internet Research, 21(5), e11705.

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