Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55939, first published .
Evaluating the Efficacy of ChatGPT as a Patient Education Tool in Prostate Cancer: Multimetric Assessment

Evaluating the Efficacy of ChatGPT as a Patient Education Tool in Prostate Cancer: Multimetric Assessment

Evaluating the Efficacy of ChatGPT as a Patient Education Tool in Prostate Cancer: Multimetric Assessment

Journals

  1. Sarikonda A, Abishek R, Isch E, Momin A, Self M, Sambangi A, Carreras A, Jallo J, Harrop J, Sivaganesan A. Assessing the Clinical Appropriateness and Practical Utility of ChatGPT as an Educational Resource for Patients Considering Minimally Invasive Spine Surgery. Cureus 2024 View
  2. Marcaccini G, Seth I, Cuomo R. Letter on: “Artificial Intelligence: Enhancing Scientific Presentations in Aesthetic Surgery”. Aesthetic Plastic Surgery 2025;49(13):3931 View
  3. Siu A, Gibson D, Chiu C, Kwok A, Irwin M, Christie A, Koh C, Keshava A, Reece M, Suen M, Rickard M. ChatGPT as a patient education tool in colorectal cancer—An in‐depth assessment of efficacy, quality and readability. Colorectal Disease 2025;27(1) View
  4. Doğan İ, Günel P, Berk İ, İpek Berk B. Evaluation of the Readability, Understandability, and Accuracy of Artificial Intelligence Chatbots in Terms of Biostatistics Literacy. European Journal of Therapeutics 2024;30(6):900 View
  5. Zitu M, Le T, Duong T, Haddadan S, Garcia M, Amorrortu R, Zhao Y, Rollison D, Thieu T. Large language models in cancer: potentials, risks, and safeguards. BJR|Artificial Intelligence 2025;2(1) View
  6. Paluszek O, Loeb S. Artificial intelligence and patient education. Current Opinion in Urology 2025;35(3):219 View
  7. Lang P, Vassar M. Addressing diversity barriers in prostate cancer clinical trials for equitable healthcare outcomes. Nature Reviews Urology 2025;22(8):493 View
  8. Tariq D, Madhusudan R, Guntupalli Y, Karumanchi Anantha Venkata Sai S, Vejandla B, LNU M. A Cross-Sectional Study Comparing Patient Information Guides for Amyotrophic Lateral Sclerosis, Myasthenia Gravis, and Guillain-Barré Syndrome Produced by ChatGPT-4 and Google Gemini 1.5. Cureus 2025 View
  9. Chen X, Xiang J, Lu S, Liu Y, He M, Shi D. Evaluating large language models and agents in healthcare: key challenges in clinical applications. Intelligent Medicine 2025;5(2):151 View
  10. Ito S, Furukawa E, Okuhara T, Okada H, Kiuchi T. Leveraging artificial intelligence chatbots for anemia prevention: A comparative study of ChatGPT-3.5, copilot, and Gemini outputs against Google Search results. PEC Innovation 2025;6:100390 View
  11. Megafu M, Guerrero O, Hasan R, Hunt L, Langhelm D, Le B, Li X, Kelly R, Parisien R, Cusano A. Evaluating the perspectives of ChatGPT and Gemini on glenohumeral osteoarthritis management. JSES International 2025;9(4):1365 View
  12. Sivanesan N, Diaz G, Kandala K, Tan W, Sprenkle P. Why prompting matters: achieving clinically accurate and consistent responses with Chat GPT. BJU International 2025;136(2):221 View
  13. van Eerde A, Teixeira A, Galletti F, Maternik M, Capone V, Westland R, Mulder J, Halbritter J, Osterholt T, Neukel V, Weber L, Liebau M, Schaefer F, Kohl S. Risks and benefits of ChatGPT in informing patients and families with rare kidney diseases: an explorative assessment by the European Rare Kidney Disease Reference Network (ERKNet). Pediatric Nephrology 2025;40(9):2899 View
  14. Owens O, Leonard M. Evaluating an AI Chatbot “Prostate Cancer Info” for Providing Quality Prostate Cancer Screening Information: Cross-Sectional Study. JMIR Cancer 2025;11:e72522 View
  15. Marcaccini G, Seth I, Lim B, Sacks B, Novo J, Ting J, Cuomo R, Rozen W. Management of Burns: Multi-Center Assessment Comparing AI Models and Experienced Plastic Surgeons. Journal of Clinical Medicine 2025;14(9):3078 View
  16. Bracey S, Bhuiyan N, Pietropaolo A, Somani B. Exploring the impact of artificial intelligence–enabled decision aids in improving patient inclusivity, empowerment, and education in urology: a systematic review by EAU endourology. Current Opinion in Urology 2025 View
  17. Luo Z, Kam S, Kim J, Hu W, Lin C, Park H, Shin Y. Does the Quality and Readability of Information Related to Varicocele Obtained from ChatGPT 4.0 Remain Consistent Across Different Models of Inquiry?. The World Journal of Men's Health 2025;43 View
  18. Krauss D, Fuchs H, Schaaf S, Drossard S, Rösch R, Blank B, Bruns C, Rolle U, Schmitz-Rixen T, Kröplin J. Ist der Einsatz digitaler Technologien der Gamechanger für die chirurgische Weiterbildung der Zukunft? Eine deutschlandweite Analyse. Die Chirurgie 2025;96(9):755 View
  19. Dastani M, Mardaneh J, Rostamian M. Large language models’ capabilities in responding to tuberculosis medical questions: testing ChatGPT, Gemini, and Copilot. Scientific Reports 2025;15(1) View
  20. Dehelean D, Maier S, Altay-Langguth A, Nitschmann A, Schmeling M, Fleischmann D, Rogowski P, Trapp C, Corradini S, Belka C, Schönecker S, Marschner S. Evaluating large language models as an educational tool for meningioma patients: patient and clinician perspectives. Radiation Oncology 2025;20(1) View
  21. Demir S, Türkeş İ. Evaluation of ChatGPT-4o, Claude 3.5 Sonnet, and Google Gemini 2.0 Flash as Patient Education Resources for Upper Blepharoplasty Patients. Journal of Craniofacial Surgery 2025;36(8):e1261 View
  22. Zhou S. Bridging knowledge gaps in breast cancer prevention: Insights from Ethiopia. World Journal of Clinical Oncology 2025;16(7) View
  23. AlGoraini Y, Alsayyali M, Alotaibi O, Almeshawi I, Alaifan F, Alrashed R. Perceptions of large language models in medical education and clinical practice among pediatric emergency physicians in Saudi Arabia: a multiregional cross-sectional study. Frontiers in Public Health 2025;13 View
  24. Umman V, Tosun B, Uygur A, Emre S. Evaluation of the Effectiveness, Safety, and Patient Satisfaction of Artificial Intelligence-Based Patient Education and Counseling for Both Recipients and Donors in the Preoperative and Postoperative Phases of Organ Transplantation. Transplantation Proceedings 2025;57(9):1832 View
  25. Choi S, Moon Y, Jung H. ChatGPT and human dietitian responses to diet-related questions on an online Q&A platform: A comparative study. DIGITAL HEALTH 2025;11 View
  26. Cheema A. The Future of Artificial Intelligence and Artificial Intelligence in Primary Care. Primary Care: Clinics in Office Practice 2025;52(4):799 View
  27. Bahir D, Hartstein M, Burkat C, Ezra D, Wulc A, Zloto O, Holds J, Hamed Azzam S. Revolutionizing Patient Education: Artificial Intelligence Versus Experts in Ocular Dyskinesia Responses. Ophthalmic Plastic & Reconstructive Surgery 2025 View
  28. Zang T, Li J, Wei L, Wang Y. Multicriteria Assessment of Text Quality in Large Language Model–Generated Gynecomastia Materials: DeepSeek Versus OpenAI Versus Claude. Journal of Craniofacial Surgery 2025 View
  29. Luo Z, Lin C, Kim T, Shin Y, Ahn S. Quality and Readability Analysis of Artificial Intelligence-Generated Medical Information Related to Prostate Cancer: A Cross-Sectional Study of ChatGPT and DeepSeek. The World Journal of Men's Health 2025;43 View
  30. Santucci J, Stapleton P, Ibrahim J, Johns‐Putra L, Elmer S, Sathianathen N. Quality of patient information on interstitial cystitis from artificial intelligence chatbots. BJU International 2025 View
  31. Qin S, Alpay E, Chislett B, Ischia J, Gibson L, Bolton D, Woon D. The Clinical Integration of ChatGPT Through an Augmented Patient Encounter in a Real-World Urological Cohort: A Feasibility Study. Société Internationale d’Urologie Journal 2025;6(5):59 View
  32. Kendir M, Zuhurlu M. Evaluation Large Language Models’ Time Dependent Consistency in Aesthetic Surgery Consultations and Comparison of Their Performance Across Different Clinical Domains. Aesthetic Plastic Surgery 2025 View
  33. Chen G, Lin C, Zhang L, Luo Z, Shin Y, Li X. Virtual case reasoning and AI-assisted diagnostic instruction: an empirical study based on body interact and large language models. BMC Medical Education 2025;25(1) View
  34. Hack S, Gvili B, Tessler I, Yogev D, Wolfowitz A, Rozendorn N. Can Chatbots Please Both Patients and Experts? Benchmarking AI and Clinical Guidelines for Hearing Loss. Otology & Neurotology 2025 View
  35. Jiang X, Liu J, Dai S, Mao X, Cha R, Wu L. Evaluating the Effectiveness of Generative AI for the Creation of Patient Education Materials on Coronary Heart Disease: A Comparative Study. JMIR Formative Research 2025;9:e78816 View
  36. Li W, Li Q. A comparative study on the application of large language models: Deepseek-R1, GPT-4o, and Claude-Sonnet-4 in post-cardiac surgery rehabilitation—A cross-sectional study. DIGITAL HEALTH 2025;11 View
  37. Mutlucan U, Bedel C, Zortuk Ö, Selvi F. EVALUATION OF READABILITY INDICES OF CHATGPT-4 AND GOOGLE GEMINI IN PATIENT EDUCATION ABOUT INTRACRANIAL HEMORRHAGES. Наука и здравоохранение 2025;(4(27)):107 View
  38. Hu J, Wang J, He L, Qiu Z, Sun S, Peng F. Evaluating the Performance of DeepSeek-R1 as a Patient Education Tool. Journal of Medical Systems 2025;49(1) View
  39. Tan S, Sng G, Lee P. Accuracy of Large Language Model Responses Versus Internet Searches for Common Questions About Glucagon-Like Peptide-1 Receptor Agonist Therapy: Exploratory Simulation Study. JMIR Formative Research 2025;9:e78289 View
  40. Mansoor I, Abdullah M, Rizwan M, Fraz M. Reasoning with large language models in medicine: a systematic review of techniques, challenges and clinical integration. Health Information Science and Systems 2025;14(1) View

Conference Proceedings

  1. Kričković E, Lukić T, Kričković Z, Stojšić-Milosavljević A, Srejić T. Planska i normativna zaštita prostora i životne sredine - zbornik radova. Use of health information systems and artificial intelligence for environmental and public health protection View