Published on in Vol 9, No 4 (2022): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35928, first published .
Natural Language Processing Methods and Bipolar Disorder: Scoping Review

Natural Language Processing Methods and Bipolar Disorder: Scoping Review

Natural Language Processing Methods and Bipolar Disorder: Scoping Review

Journals

  1. Pollock Star A, Bachner Y, Cohen B, Haglili O, O'Rourke N. Social Media Use and Well-being With Bipolar Disorder During the COVID-19 Pandemic: Path Analysis. JMIR Formative Research 2022;6(8):e39519 View
  2. Loch A, Lopes-Rocha A, Ara A, Gondim J, Cecchi G, Corcoran C, Mota N, Argolo F. Ethical Implications of the Use of Language Analysis Technologies for the Diagnosis and Prediction of Psychiatric Disorders. JMIR Mental Health 2022;9(11):e41014 View
  3. Benítez-Andrades J, García-Ordás M, Russo M, Sakor A, Fernandes Rotger L, Vidal M, Kondylakis H, Rao P, Stefanidis K. Empowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media posts. Semantic Web 2023;14(5):873 View
  4. Zhu Q, Xiong J, Peng L. College students’ mental health evaluation model based on tensor fusion network with multimodal data during the COVID-19 pandemic. Biotechnology and Genetic Engineering Reviews 2024;40(3):1821 View
  5. Liang Y, Liu L, Ji Y, Huangfu L, Zeng D. Identifying emotional causes of mental disorders from social media for effective intervention. Information Processing & Management 2023;60(4):103407 View
  6. Gebremeskel H, Chong F, Heyan H. Unlock Tigrigna NLP: Design and Development of Morphological Analyzer for Tigrigna Verbs Using Hybrid Approach. SSRN Electronic Journal 2023 View
  7. Yoon M, Park J, Hur T, Hua C, Hussain M, Lee S, Choi D. Application and Potential of Artificial Intelligence in Heart Failure: Past, Present, and Future. International Journal of Heart Failure 2024;6(1):11 View
  8. Zhou B, Yang G, Shi Z, Ma S. Natural Language Processing for Smart Healthcare. IEEE Reviews in Biomedical Engineering 2024;17:4 View
  9. Ma S, Jiang S, Yang O, Zhang X, Fu Y, Zhang Y, Kaareen A, Ling M, Chen J, Shang C. Use of Machine Learning Tools in Evidence Synthesis of Tobacco Use Among Sexual and Gender Diverse Populations: Algorithm Development and Validation. JMIR Formative Research 2024;8:e49031 View
  10. Villarreal-Zegarra D, Reategui-Rivera C, García-Serna J, Quispe-Callo G, Lázaro-Cruz G, Centeno-Terrazas G, Galvez-Arevalo R, Escobar-Agreda S, Dominguez-Rodriguez A, Finkelstein J. Self-Administered Interventions Based on Natural Language Processing Models for Reducing Depressive and Anxiety Symptoms: Systematic Review and Meta-Analysis. JMIR Mental Health 2024;11:e59560 View
  11. Seepold R, Scherz W, Vélez D, Echeverry-Correa J, Ávila-Campos J, Gómez-Suta M. A Conceptual Vision of Early Detection of Impulse Control Disorders in Pediatric Populations via Speech and Sleep Pattern Analysis. Procedia Computer Science 2024;246:4646 View
  12. Holmes G, Tang B, Gupta S, Venkatesh S, Christensen H, Whitton A. Applications of Large Language Models in the Field of Suicide Prevention: A Scoping Review (Preprint). Journal of Medical Internet Research 2024 View

Books/Policy Documents

  1. Safa R, Edalatpanah S, Sorourkhah A. Deep Learning in Personalized Healthcare and Decision Support. View