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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15589, first published .
An Exploration Into the Use of a Chatbot for Patients With Inflammatory Bowel Diseases: Retrospective Cohort Study

An Exploration Into the Use of a Chatbot for Patients With Inflammatory Bowel Diseases: Retrospective Cohort Study

An Exploration Into the Use of a Chatbot for Patients With Inflammatory Bowel Diseases: Retrospective Cohort Study

Journals

  1. Egli A, Schrenzel J, Greub G. Digital microbiology. Clinical Microbiology and Infection 2020;26(10):1324 View
  2. Cohen‐Mekelburg S, Berry S, Stidham R, Zhu J, Waljee A. Clinical applications of artificial intelligence and machine learning‐based methods in inflammatory bowel disease. Journal of Gastroenterology and Hepatology 2021;36(2):279 View
  3. McKillop M, South B, Preininger A, Mason M, Jackson G. Leveraging conversational technology to answer common COVID-19 questions. Journal of the American Medical Informatics Association 2021;28(4):850 View
  4. Lee H, Kang J, Yeo J. Medical Specialty Recommendations by an Artificial Intelligence Chatbot on a Smartphone: Development and Deployment. Journal of Medical Internet Research 2021;23(5):e27460 View
  5. Schick A, Feine J, Morana S, Maedche A, Reininghaus U. Validity of Chatbot Use for Mental Health Assessment: Experimental Study. JMIR mHealth and uHealth 2022;10(10):e28082 View
  6. Stidham R, Takenaka K. Artificial Intelligence for Disease Assessment in Inflammatory Bowel Disease: How Will it Change Our Practice?. Gastroenterology 2022;162(5):1493 View
  7. Chen J, Baxter S. Applications of natural language processing in ophthalmology: present and future. Frontiers in Medicine 2022;9 View
  8. Brooks-Warburton J, Ashton J, Dhar A, Tham T, Allen P, Hoque S, Lovat L, Sebastian S. Artificial intelligence and inflammatory bowel disease: practicalities and future prospects. Frontline Gastroenterology 2022;13(4):325 View
  9. Pernencar C, Saboia I, Dias J. How Far Can Conversational Agents Contribute to IBD Patient Health Care—A Review of the Literature. Frontiers in Public Health 2022;10 View
  10. Kocaballi A, Sezgin E, Clark L, Carroll J, Huang Y, Huh-Yoo J, Kim J, Kocielnik R, Lee Y, Mamykina L, Mitchell E, Moore R, Murali P, Mynatt E, Park S, Pasta A, Richards D, Silva L, Smriti D, Spillane B, Zhang Z, Zubatiy T. Design and Evaluation Challenges of Conversational Agents in Health Care and Well-being: Selective Review Study. Journal of Medical Internet Research 2022;24(11):e38525 View
  11. Chua J, Choolani M, Chee C, Chan Y, Lalor J, Chong Y, Shorey S. Insights of Parents and Parents‐To‐Be in Using Chatbots to Improve Their Preconception, Pregnancy, and Postpartum Health: A Mixed Studies Review. Journal of Midwifery & Women's Health 2023;68(4):480 View
  12. Rani S, Jain A. Optimizing healthcare system by amalgamation of text processing and deep learning: a systematic review. Multimedia Tools and Applications 2024;83(1):279 View
  13. Feldman K, Nehme F. Beyond Clinical Accuracy: Considerations for the Use of Generative Artificial Intelligence Models in Gastrointestinal Care. Gastroenterology 2023;165(2):336 View
  14. Thaxton C, Dardik A. Computer Science meets Vascular Surgery: Keeping a pulse on artificial intelligence. Seminars in Vascular Surgery 2023;36(3):419 View
  15. Padoan A, Musso G, Contran N, Basso D. Inflammation, Autoinflammation and Autoimmunity in Inflammatory Bowel Diseases. Current Issues in Molecular Biology 2023;45(7):5534 View
  16. Patil N, Huang R, van der Pol C, Larocque N. Comparative Performance of ChatGPT and Bard in a Text-Based Radiology Knowledge Assessment. Canadian Association of Radiologists Journal 2024;75(2):344 View
  17. Griffin A, Khairat S, Bailey S, Chung A. A chatbot for hypertension self-management support: user-centered design, development, and usability testing. JAMIA Open 2023;6(3) View
  18. Ferro Desideri L, Roth J, Zinkernagel M, Anguita R. Application and accuracy of artificial intelligence-derived large language models in patients with age related macular degeneration. International Journal of Retina and Vitreous 2023;9(1) View
  19. Pinton P. Impact of artificial intelligence on prognosis, shared decision-making, and precision medicine for patients with inflammatory bowel disease: a perspective and expert opinion. Annals of Medicine 2023;55(2) View
  20. Amin Kuhail M, Bahja M, Al-Shamaileh O, Thomas J, Alkazemi A, Negreiros J. Assessing the Impact of Chatbot-Human Personality Congruence on User Behavior: A Chatbot-Based Advising System Case. IEEE Access 2024;12:71761 View
  21. Rojas-Carabali W, Agrawal R, Gutierrez-Sinisterra L, Baxter S, Cifuentes-González C, Wei Y, Abisheganaden J, Kannapiran P, Wong S, Lee B, de-la-Torre A, Agrawal R. Natural Language Processing in medicine and ophthalmology: A review for the 21st-century clinician. Asia-Pacific Journal of Ophthalmology 2024;13(4):100084 View
  22. Sharma N, Wrede C, Bastoni S, Braakman-Jansen A, van Gemert-Pijnen L. A digital informal care support platform: Lessons learned from a multi-method study on continued implementation and support functionality use before and after Covid-19 (Preprint). JMIR Formative Research 2023 View
  23. Chung K. The evolution of creativity: how generative AI is reshaping the hospitality landscape. Enterprise Information Systems 2024 View
  24. Lavadi R, Carnovale B, Tirmizi Z, Gajjar A, Kumar R, Shah M, Hamilton D, Agarwal N. Examining the Readability of AtlasGPT, the Premiere Resource for Neurosurgical Education. World Neurosurgery 2024 View

Books/Policy Documents

  1. de Oliveira E, Spalenza M, Pirovani J. Intelligent Systems Design and Applications. View
  2. Drozda P, Sopyła K. Artificial Intelligence and Soft Computing. View
  3. Zwicky A, Stallone V, Haarmann J. Information Systems and Technologies. View