Published on in Vol 22, No 5 (2020): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15371, first published .
Transfer Learning for Risk Classification of Social Media Posts: Model Evaluation Study

Transfer Learning for Risk Classification of Social Media Posts: Model Evaluation Study

Transfer Learning for Risk Classification of Social Media Posts: Model Evaluation Study

Journals

  1. Skaik R, Inkpen D. Using Social Media for Mental Health Surveillance. ACM Computing Surveys 2021;53(6):1 View
  2. Li J, Lu J, Chen C, Ma J, Liao X. Tool wear state prediction based on feature-based transfer learning. The International Journal of Advanced Manufacturing Technology 2021;113(11-12):3283 View
  3. Arpaci I. Predicting problematic smartphone use based on early maladaptive schemas by using machine learning classification algorithms. Journal of Rational-Emotive & Cognitive-Behavior Therapy 2023;41(3):634 View
  4. de Pablo Á, Araque O, Iglesias C. Transfer Learning with Social Media Content in the Ride-Hailing Domain by Using a Hybrid Machine Learning Architecture. Electronics 2022;11(2):189 View
  5. Ebbehoj A, Thunbo M, Andersen O, Glindtvad M, Hulman A, Chua Chin Heng M. Transfer learning for non-image data in clinical research: A scoping review. PLOS Digital Health 2022;1(2):e0000014 View
  6. 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
  7. Skaik R, Inkpen D. Predicting Depression in Canada by Automatic Filling of Beck’s Depression Inventory Questionnaire. IEEE Access 2022;10:102033 View
  8. Manduchi E, Romano J, Moore J. The promise of automated machine learning for the genetic analysis of complex traits. Human Genetics 2022;141(9):1529 View
  9. Chen Y, Chu Y, Huang C, Lee Y, Lee W, Hsu C, Yang A, Liao W, Cheng Y. Smartphone-based artificial intelligence using a transfer learning algorithm for the detection and diagnosis of middle ear diseases: A retrospective deep learning study. eClinicalMedicine 2022;51:101543 View
  10. Wu E, Wu C, Lee M, Chu K, Huang M. Development of Internet suicide message identification and the Monitoring-Tracking-Rescuing model in Taiwan. Journal of Affective Disorders 2023;320:37 View
  11. Schindler M, Domahidi E. The computational turn in online mental health research: A systematic review. New Media & Society 2023;25(10):2781 View
  12. Nasrullah S, Jalali A, Koundal D. Detection of Types of Mental Illness through the Social Network Using Ensembled Deep Learning Model. Computational Intelligence and Neuroscience 2022;2022:1 View
  13. Garg S, Taylor J, El Sherief M, Kasson E, Aledavood T, Riordan R, Kaiser N, Cavazos-Rehg P, De Choudhury M. Detecting risk level in individuals misusing fentanyl utilizing posts from an online community on Reddit. Internet Interventions 2021;26:100467 View
  14. Crema C, Attardi G, Sartiano D, Redolfi A. Natural language processing in clinical neuroscience and psychiatry: A review. Frontiers in Psychiatry 2022;13 View
  15. Sarupuri B, Kulpa R, Aristidou A, Multon F. Dancing in virtual reality as an inclusive platform for social and physical fitness activities: a survey. The Visual Computer 2024;40(6):4055 View
  16. Zhao Y, Liu D, Wan C, Liu X, Nie J, Liu J. JMS-QA: A Joint Hierarchical Architecture for Mental Health Question Answering. IEEE/ACM Transactions on Audio, Speech, and Language Processing 2024;32:352 View
  17. Khan A, Ali R. Unraveling minds in the digital era: a review on mapping mental health disorders through machine learning techniques using online social media. Social Network Analysis and Mining 2024;14(1) View
  18. Houssein E, Mohamed R, Hu G, Ali A. Adapting transformer-based language models for heart disease detection and risk factors extraction. Journal of Big Data 2024;11(1) View

Books/Policy Documents

  1. Ananthanagu U, Agarwal P. Intelligent Sustainable Systems. View
  2. Moore J, Ribeiro P, Matsumoto N, Saini A. Handbook of Evolutionary Machine Learning. View
  3. Moore J, Ribeiro P, Matsumoto N, Saini A. Clinical Applications of Artificial Intelligence in Real-World Data. View