Published on in Vol 20 , No 6 (2018) :June

Journals
- Oexle N, Niederkrotenthaler T, DeLeo D. Emerging trends in suicide prevention research. Current Opinion in Psychiatry 2019;32(4):336 View
- Tadesse M, Lin H, Xu B, Yang L. Detection of Suicide Ideation in Social Media Forums Using Deep Learning. Algorithms 2019;13(1):7 View
- Zunic A, Corcoran P, Spasic I. Sentiment Analysis in Health and Well-Being: Systematic Review. JMIR Medical Informatics 2020;8(1):e16023 View
- Cacheda F, Fernandez D, Novoa F, Carneiro V. Early Detection of Depression: Social Network Analysis and Random Forest Techniques. Journal of Medical Internet Research 2019;21(6):e12554 View
- Bernert R, Hilberg A, Melia R, Kim J, Shah N, Abnousi F. Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations. International Journal of Environmental Research and Public Health 2020;17(16):5929 View
- Chancellor S, De Choudhury M. Methods in predictive techniques for mental health status on social media: a critical review. npj Digital Medicine 2020;3(1) View
- Shen Y, Zhang W, Chan B, Zhang Y, Meng F, Kennon E, Wu H, Luo X, Zhang X. Detecting risk of suicide attempts among Chinese medical college students using a machine learning algorithm. Journal of Affective Disorders 2020;273:18 View
- Strand M, Gustafsson S. Mukbang and Disordered Eating: A Netnographic Analysis of Online Eating Broadcasts. Culture, Medicine, and Psychiatry 2020;44(4):586 View
- Soron T, Shariful Islam S. Suicide on Facebook-the tales of unnoticed departure in Bangladesh. Global Mental Health 2020;7 View
- Davis , Sedig , Lizotte . Archetype-Based Modeling and Search of Social Media. Big Data and Cognitive Computing 2019;3(3):44 View
- Fonseka T, Bhat V, Kennedy S. The utility of artificial intelligence in suicide risk prediction and the management of suicidal behaviors. Australian & New Zealand Journal of Psychiatry 2019;53(10):954 View
- Yao H, Rashidian S, Dong X, Duanmu H, Rosenthal R, Wang F. Detection of Suicidality Among Opioid Users on Reddit: Machine Learning–Based Approach. Journal of Medical Internet Research 2020;22(11):e15293 View
- Liu D, Fu Q, Wan C, Liu X, Jiang T, Liao G, Qiu X, Liu R. Suicidal Ideation Cause Extraction From Social Texts. IEEE Access 2020;8:169333 View
- Garg S, Raigosa A, Aiman R. Investigating differential linguistic patterns exhibited by Major Depressive Disorder (MDD) Patients and building a Long Short Term Memory Network + Convolutional Neural Network Model, Logistic Regression model, and a Multinomial Naive Bayes Classifier Algorithm to develop Spero, a hybrid app based Early-MDD diagnosis system. International Journal of Scientific Research in Computer Science, Engineering and Information Technology 2020:114 View
- Forte A, Sarli G, Polidori L, Lester D, Pompili M. The Role of New Technologies to Prevent Suicide in Adolescence: A Systematic Review of the Literature. Medicina 2021;57(2):109 View
- Skaik R, Inkpen D. Using Social Media for Mental Health Surveillance. ACM Computing Surveys 2021;53(6):1 View
- Ji S, Pan S, Li X, Cambria E, Long G, Huang Z. Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications. IEEE Transactions on Computational Social Systems 2021;8(1):214 View
- Mason A, Jang K, Morley K, Scarf D, Collings S, Riordan B. A Content Analysis of Reddit Users' Perspectives on Reasons for Not Following Through with a Suicide Attempt. Cyberpsychology, Behavior, and Social Networking 2021;24(10):642 View
- López-Úbeda P, Plaza-del-Arco F, Díaz-Galiano M, Martín-Valdivia M. How Successful Is Transfer Learning for Detecting Anorexia on Social Media?. Applied Sciences 2021;11(4):1838 View
- Cheng Q, Lui C. Applying text mining methods to suicide research. Suicide and Life-Threatening Behavior 2021;51(1):137 View
- S S, S. Raj J. Analysis of Deep Learning Techniques for Early Detection of Depression on Social Media Network - A Comparative Study. Journal of Trends in Computer Science and Smart Technology 2021;3(1):24 View
- Lekkas D, Klein R, Jacobson N. Predicting acute suicidal ideation on Instagram using ensemble machine learning models. Internet Interventions 2021;25:100424 View
- Arillotta D, Guirguis A, Corkery J, Scherbaum N, Schifano F. COVID-19 Pandemic Impact on Substance Misuse: A Social Media Listening, Mixed Method Analysis. Brain Sciences 2021;11(7):907 View
- Silveira B, Silva H, Murai F, da Silva A. Predicting user emotional tone in mental disorder online communities. Future Generation Computer Systems 2021;125:641 View
- Xu X. Detecting Suicide Ideation in the Online Environment: A Survey of Methods and Challenges. IEEE Transactions on Computational Social Systems 2022;9(3):679 View
- Haque R, Islam N, Islam M, Ahsan M. A Comparative Analysis on Suicidal Ideation Detection Using NLP, Machine, and Deep Learning. Technologies 2022;10(3):57 View
- Zhang T, Schoene A, Ji S, Ananiadou S. Natural language processing applied to mental illness detection: a narrative review. npj Digital Medicine 2022;5(1) View
- Ungless E, Ross B, Belle V. Potential Pitfalls With Automatic Sentiment Analysis: The Example of Queerphobic Bias. Social Science Computer Review 2023:089443932311529 View
- Fukazawa Y. Estimating Mental Health Using Human-generated Big Data and Machine Learning. The Brain & Neural Networks 2022;29(2):78 View
- Garg M. Mental Health Analysis in Social Media Posts: A Survey. Archives of Computational Methods in Engineering 2023;30(3):1819 View
- Tejaswini V, Babu K, Sahoo B. Depression Detection from Social Media Text Analysis using Natural Language Processing Techniques and Hybrid Deep Learning Model. ACM Transactions on Asian and Low-Resource Language Information Processing 2022 View
- Yeskuatov E, Chua S, Foo L. Leveraging Reddit for Suicidal Ideation Detection: A Review of Machine Learning and Natural Language Processing Techniques. International Journal of Environmental Research and Public Health 2022;19(16):10347 View
- Chancellor S, Sumner S, David-Ferdon C, Ahmad T, De Choudhury M. Suicide Risk and Protective Factors in Online Support Forum Posts: Annotation Scheme Development and Validation Study. JMIR Mental Health 2021;8(11):e24471 View
- Huang Y, Zhu C, Feng Y, Ji Y, Song J, Wang K, Yu F. Comparison of three machine learning models to predict suicidal ideation and depression among Chinese adolescents: A cross-sectional study. Journal of Affective Disorders 2022;319:221 View
- Wang R, Yang B, Ma Y, Wang P, Yu Q, Zong X, Huang Z, Ma S, Hu L, Hwang K, Liu Z. Medical-Level Suicide Risk Analysis: A Novel Standard and Evaluation Model. IEEE Internet of Things Journal 2021;8(23):16825 View
- Homan S, Gabi M, Klee N, Bachmann S, Moser A, Duri' M, Michel S, Bertram A, Maatz A, Seiler G, Stark E, Kleim B. Linguistic features of suicidal thoughts and behaviors: A systematic review. Clinical Psychology Review 2022;95:102161 View
- Renjith S, Abraham A, Jyothi S, Chandran L, Thomson J. An ensemble deep learning technique for detecting suicidal ideation from posts in social media platforms. Journal of King Saud University - Computer and Information Sciences 2022;34(10):9564 View
- Kodati D, Tene R. Identifying suicidal emotions on social media through transformer-based deep learning. Applied Intelligence 2023;53(10):11885 View
- Cao X, Liu X. Artificial intelligence-assisted psychosis risk screening in adolescents: Practices and challenges. World Journal of Psychiatry 2022;12(10):1287 View
- Liu J, Shi M, Jiang H. Detecting Suicidal Ideation in Social Media: An Ensemble Method Based on Feature Fusion. International Journal of Environmental Research and Public Health 2022;19(13):8197 View
- Zhang T, Yang K, Ji S, Ananiadou S. Emotion fusion for mental illness detection from social media: A survey. Information Fusion 2023;92:231 View
- Mandryk R, Birk M, Vedress S, Wiley K, Reid E, Berger P, Frommel J. Remote Assessment of Depression Using Digital Biomarkers From Cognitive Tasks. Frontiers in Psychology 2021;12 View
- Ptaszynski M, Zasko-Zielinska M, Marcinczuk M, Leliwa G, Fortuna M, Soliwoda K, Dziublewska I, Hubert O, Skrzek P, Piesiewicz J, Karbowska P, Dowgiallo M, Eronen J, Tempska P, Brochocki M, Godny M, Wroczynski M. Looking for Razors and Needles in a Haystack: Multifaceted Analysis of Suicidal Declarations on Social Media—A Pragmalinguistic Approach. International Journal of Environmental Research and Public Health 2021;18(22):11759 View
- Gupta D, Markale A, Kulkarni R. Mental Health Quantifier. International Journal of Engineering and Advanced Technology 2021;10(5):187 View
- Gu Y, Chen D, Liu X. Suicide Possibility Scale Detection via Sina Weibo Analytics: Preliminary Results. International Journal of Environmental Research and Public Health 2022;20(1):466 View
- Smrke U, Mlakar I, Lin S, Musil B, Plohl N. Language, Speech, and Facial Expression Features for Artificial Intelligence–Based Detection of Cancer Survivors’ Depression: Scoping Meta-Review. JMIR Mental Health 2021;8(12):e30439 View
- Aldhyani T, Alsubari S, Alshebami A, Alkahtani H, Ahmed Z. Detecting and Analyzing Suicidal Ideation on Social Media Using Deep Learning and Machine Learning Models. International Journal of Environmental Research and Public Health 2022;19(19):12635 View
- Amanat A, Rizwan M, Javed A, Abdelhaq M, Alsaqour R, Pandya S, Uddin M. Deep Learning for Depression Detection from Textual Data. Electronics 2022;11(5):676 View
- Sami Khafaga D, Auvdaiappan M, Deepa K, Abouhawwash M, Khalid Karim F. Deep Learning for Depression Detection Using Twitter Data. Intelligent Automation & Soft Computing 2023;36(2):1301 View
- Rabani S, Ud Din Khanday A, Khan Q, Hajam U, Imran A, Kastrati Z. Detecting suicidality on social media: Machine learning at rescue. Egyptian Informatics Journal 2023;24(2):291 View
Books/Policy Documents
- Andavar V, Gupta S. Bio-Inspired Algorithms and Devices for Treatment of Cognitive Diseases Using Future Technologies. View
- Mantilla-Saavedra C, Gutiérrez-Cárdenas J. Information Management and Big Data. View
- Madkar S, Maheshwari T, Merani M, Merchant R, Doshi P. Advances in Computing and Data Sciences. View
- Jyothi S, Renjith S. Advances in Data and Information Sciences. View
- Verma A, Harper M, Assi S, Al-Hamid A, Yousif M, Mustafina J, Ismail N, Al-Jumeily OBE D. Data Science and Emerging Technologies. View
- Denecke K. Sentiment Analysis in the Medical Domain. View
- Denecke K. Sentiment Analysis in the Medical Domain. View