REFERENCES
2. Gould H, Sohail OA, Haines CM. Anterior cervical discectomy and fusion: techniques, complications, and future directives. Semin Spine Surg 2020;32:100772.
3. Gaudin D, Krafcik BM, Mansour TR, Alnemari A. Considerations in spinal fusion surgery for chronic lumbar pain: psychosocial factors, rating scales, and perioperative patient education - a review of the literature. World Neurosurg 2017;98:21-7.
4. Cline RJ, Haynes KM. Consumer health information seeking on the Internet: the state of the art. Health Educ Res 2001;16:671-92.
5. Langford AT, Roberts T, Gupta J, Orellana KT, Loeb S. Impact of the Internet on patient-physician communication. Eur Urol Focus 2020;6:440-4.
6. Thirunavukarasu AJ, Ting DSJ, Elangovan K, Gutierrez L, Tan TF, Ting DSW. Large language models in medicine. Nat Med 2023;29:1930-40.
7. Hung YC, Chaker SC, Sigel M, Saad M, Slater ED. Comparison of patient education materials generated by chat generative pre-trained transformer versus experts: an innovative way to increase readability of patient education materials. Ann Plast Surg 2023;91:409-12.
8. Lang SP, Yoseph ET, Gonzalez-Suarez AD, et al. Analyzing large language models’ responses to common lumbar spine fusion surgery questions: a comparison between ChatGPT and Bard. Neurospine 2024;21:633-41.
9. Blease C, Bernstein MH, Gaab J, et al. Computerization and the future of primary care: a survey of general practitioners in the UK. PLoS One 2018;13:e0207418.
10. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977;33:159-74.
11. Goodman RS, Patrinely JR, Stone CA Jr, et al. Accuracy and reliability of chatbot responses to physician questions. JAMA Netw Open 2023;6:e2336483.
12. Subramanian T, Shahi P, Araghi K, et al. Using artificial intelligence to answer common patient-focused questions in minimally invasive spine surgery. J Bone Joint Surg Am 2023;105:1649-53.
13. Mika AP, Martin JR, Engstrom SM, Polkowski GG, Wilson JM. Assessing ChatGPT responses to common patient questions regarding total hip arthroplasty. J Bone Joint Surg Am 2023;105:1519-26.
14. Jahanshahi H, Kazmi S, Cevik M. Auto response generation in online medical chat services. J Healthc Inform Res 2022;6:344-74.
15. Aggarwal A, Tam CC, Wu D, Li X, Qiao S. Artificial intelligence-based chatbots for promoting health behavioral changes: systematic review. J Med Internet Res 2023;25:e40789.
16. Bharti U, Bajaj D, Batra H, Lalit S, Lalit S, Gangwani A. Medbot: conversational artificial intelligence powered chatbot for delivering tele-health after COVID-19. In: 2020 5th International Conference on Communication and Electronics Systems (ICCES); 2020 Jun 10-12; Coimbatore, India. IEEE; 2020. pp. 870-5.
17. Laranjo L, Dunn AG, Tong HL, et al. Conversational agents in healthcare: a systematic review. J Am Med Inform Assoc 2018;25:1248-58.
18. OpenAI. GPT-4. Available from: https://openai.com/gpt-4. [Last accessed on 27 Sep 2024].
19. OpenAI. GPT-4 Research. Available from: https://openai.com/index/gpt-4-research/. [Last accessed on 27 Sep 2024].
20. Brin D, Sorin V, Vaid A, et al. Comparing ChatGPT and GPT-4 performance in USMLE soft skill assessments. Sci Rep 2023;13:16492.
21. Sharma A, Schauer DP, Kelleher M, Kinnear B, Sall D, Warm E. USMLE step 2 CK: best predictor of multimodal performance in an internal medicine residency. J Grad Med Educ 2019;11:412-9.
22. Ayers JW, Poliak A, Dredze M, et al. Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum. JAMA Intern Med 2023;183:589-96.
23. Ali R, Connolly ID, Tang OY, et al. Bridging the literacy gap for surgical consents: an AI-human expert collaborative approach. NPJ Digit Med 2024;7:63.
