Page 160 - Handbook of Deep Learning in Biomedical Engineering Techniques and Applications

Chapter 5 Depression discovery in cancer communities using deep learning 149

References

[1] https://www.who.int/news-room/fact-sheets/detail/cancer.
[2] American Psychiatric Association, Diagnostic and Statistical Manual of
Mental Disorders, fifth ed., American Psychiatric Publishing, Washington,
2013.
[3] D. Ramalingam, V. Sharma, P. Zar, Study of depression analysis using
machine learning techniques, Int. J. Innov. Technol. Explor. Eng. 8 (7C2)
(May 2019). ISSN: 2278e3075.
[4] W.C. Crannell, E. Clark, C. Jones, T.A. James, J. Moore, A pattern-matched
Twitter analysis of US cancer-patient sentiments, J. Surg. Res. 206 (2) (2016)
536e542.
[5] W. Medhat, A. Hassan, H. Korashy, Sentiment analysis algorithms and
applications: a survey, Ain Shams Eng. J. 5 (4) (December 2014) 1093e1113.
[6] S. Vashishtha, S. Susan, Fuzzy rule based unsupervised sentiment analysis
from social media posts, Expert Syst. Appl. 138 (30) (December 2019)
112834.
[7] S. Sharma, S. Chakraverty, A. Sharma, J. Kaur, A context based algorithm for
sentiment analysis, Int. J. Comput. Vis. Robot. 7 (5) (2017). InderScience
Publishers.
[8] N. Nigam, D. Yadav, Lexicon-based approach to sentiment analysis of
tweets using R language, in: International Conference on Advances in
Computing and Data Sciences, ICACDS, Adv. Comput. Data Sci., 2018,
pp. 154e164.
[9] S. Almatarneh, P. Gamallo, A lexicon based method to search for extreme
opinions, PLoS One 13 (5) (2018) e0197816, https://doi.org/10.1371/
journal.pone.019781.
[10] H. Minging, B. Liu, Mining and summarizing customer reviews, in:
Proceedings of ACM SIGKDD International Conference on Knowledge
Discovery and Data Mining, 2004.
[11] S. Kim, E. Hovy, Determining the sentiment of opinions, in: Proceedings of
International Conference on Computational Linguistics, Coling, 2004,
pp. 1367e1373.
[12] S. Mohammad, C. Dunne, B. Dorr, Generating high-coverage semantic
orientation lexicons from overly marked words and a thesaurus, in:
Proceedings of the Conference on Empirical Methods in Natural Language
Processing, 2009.
[13] S. Park, Y. Kim, Building thesaurus lexicon using dictionary-based approach
for sentiment classification, in: IEEE 14th International Conference on
Software Engineering Research, Management and Applications (SERA),
Towson, MD, USA, 2016.
[14] V. Hatzivassiloglou, K. McKeown, Predicting the semantic orientation of
adjectives, in: Proceedings of Annual Meeting of Association of
Computational Linguistics, 1997.
[15] F.L. Cruz, J.A. Troyano, F. Enrı quez, O.F. Javier, C.G. Vallejo, Long
autonomy or long delay? The importance of domain in opinion mining,
Expert Syst. Appl. 40 (2013) 3174e3184.
[16] A. Fahrni, M. Klenner, Old wine or warm beer: target-specific sentiment
analysis of adjectives, in: Proceedings of the Symposium on Affective
Language in Human and Machine, AISB, 2008.