Published on in Vol 8, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16862, first published .
Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and Usability Study

Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and Usability Study

Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and Usability Study

Journals

  1. Nimmanterdwong Z, Boonviriya S, Tangkijvanich P. Human-Centered Design of Mobile Health Apps for Older Adults: Systematic Review and Narrative Synthesis. JMIR mHealth and uHealth 2022;10(1):e29512 View
  2. Chen J, Baxter S. Applications of natural language processing in ophthalmology: present and future. Frontiers in Medicine 2022;9 View
  3. Wang Q, Liu J, Zhou L, Tian J, Chen X, Zhang W, Wang H, Zhou W, Gao Y. Usability evaluation of mHealth apps for elderly individuals: a scoping review. BMC Medical Informatics and Decision Making 2022;22(1) View
  4. Wang L, Zhang Y, Chignell M, Shan B, Sheehan K, Razak F, Verma A. Boosting Delirium Identification Accuracy With Sentiment-Based Natural Language Processing: Mixed Methods Study. JMIR Medical Informatics 2022;10(12):e38161 View
  5. Nawaz F, Barr A, Desai M, Tsagkaris C, Singh R, Klager E, Eibensteiner F, Parvanov E, Hribersek M, Kletecka-Pulker M, Willschke H, Atanasov A. Promoting Research, Awareness, and Discussion on AI in Medicine Using #MedTwitterAI: A Longitudinal Twitter Hashtag Analysis. Frontiers in Public Health 2022;10 View
  6. Skeen S, Jones S, Cruse C, Horvath K. Integrating Natural Language Processing and Interpretive Thematic Analyses to Gain Human-Centered Design Insights on HIV Mobile Health: Proof-of-Concept Analysis. JMIR Human Factors 2022;9(3):e37350 View
  7. Anmella G, Sanabra M, Primé-Tous M, Segú X, Cavero M, Morilla I, Grande I, Ruiz V, Mas A, Martín-Villalba I, Caballo A, Esteva J, Rodríguez-Rey A, Piazza F, Valdesoiro F, Rodriguez-Torrella C, Espinosa M, Virgili G, Sorroche C, Ruiz A, Solanes A, Radua J, Also M, Sant E, Murgui S, Sans-Corrales M, H Young A, Vicens V, Blanch J, Caballeria E, López-Pelayo H, López C, Olivé V, Pujol L, Quesada S, Solé B, Torrent C, Martínez-Aran A, Guarch J, Navinés R, Murru A, Fico G, de Prisco M, Oliva V, Amoretti S, Pio-Carrino C, Fernández-Canseco M, Villegas M, Vieta E, Hidalgo-Mazzei D. Vickybot, a Chatbot for Anxiety-Depressive Symptoms and Work-Related Burnout in Primary Care and Health Care Professionals: Development, Feasibility, and Potential Effectiveness Studies. Journal of Medical Internet Research 2023;25:e43293 View
  8. Chen Z, Xiao F, Wang Y, Wang Y, Hou W, Wang J, Li L. Online review analysis-based multi-criteria decision-making for evaluating patient satisfaction: A case study of the Haodf website. Journal of the Operational Research Society 2024;75(5):841 View
  9. Zargaran D, Zargaran A, Sousi S, Knight D, Cook H, Woollard A, Davies J, Weyrich T, Mosahebi A. Quantitative and qualitative analysis of individual experiences post botulinum toxin injection ‐ United Kingdom Survey. Skin Health and Disease 2023;3(5) View
  10. CERRITO A, SCHMITT K. Exploring end users' perspectives for the development of an injury surveillance system in Swiss Olympic wrestling. Gazzetta Medica Italiana Archivio per le Scienze Mediche 2023;182(9) View
  11. Aljamaan F, Malki K, Alhasan K, Jamal A, Altamimi I, Khayat A, Alhaboob A, Abdulmajeed N, Alshahrani F, Saad K, Al-Eyadhy A, Al-Tawfiq J, Temsah M. ChatGPT-3.5 System Usability Scale early assessment among Healthcare Workers: Horizons of adoption in medical practice. Heliyon 2024;10(7):e28962 View
  12. Huisman T, Huisman T. Artificial Intelligence in Newborn Medicine. Newborn 2024;3(2):96 View

Books/Policy Documents

  1. Mukhopadhyay J, Ghosh A. Big Data Analytics in Cognitive Social Media and Literary Texts. View