Published on in Vol 11 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53559, first published .
The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research

The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research

The Temperature Feature of ChatGPT: Modifying Creativity for Clinical Research

Journals

  1. Jalali M, Akhavan A. Integrating AI language models in qualitative research: Replicating interview data analysis with ChatGPT. System Dynamics Review 2024;40(3) View
  2. Ömür Arça D, Erdemir İ, Kara F, Shermatov N, Odacioğlu M, İbişoğlu E, Hanci F, Sağiroğlu G, Hanci V. Assessing the readability, reliability, and quality of artificial intelligence chatbot responses to the 100 most searched queries about cardiopulmonary resuscitation: An observational study. Medicine 2024;103(22):e38352 View
  3. Dehdab R, Brendlin A, Werner S, Almansour H, Gassenmaier S, Brendel J, Nikolaou K, Afat S. Evaluating ChatGPT-4V in chest CT diagnostics: a critical image interpretation assessment. Japanese Journal of Radiology 2024;42(10):1168 View
  4. Lin A, Zhu L, Mou W, Yuan Z, Cheng Q, Jiang A, Luo P. Advancing generative artificial intelligence in medicine: recommendations for standardized evaluation. International Journal of Surgery 2024;110(8):4547 View
  5. Banik D, Pati N, Sharma A. Systematic exploration and in-depth analysis of ChatGPT architectures progression. Artificial Intelligence Review 2024;57(10) View
  6. Qu Y, Wang J. Performance and biases of Large Language Models in public opinion simulation. Humanities and Social Sciences Communications 2024;11(1) View
  7. Makhortykh M, Sydorova M, Baghumyan A, Vziatysheva V, Kuznetsova E. Stochastic lies: How LLM-powered chatbots deal with Russian disinformation about the war in Ukraine. Harvard Kennedy School Misinformation Review 2024 View
  8. Mankowski M, Jaffe I, Xu J, Bae S, Oermann E, Aphinyanaphongs Y, McAdams‐DeMarco M, Lonze B, Orandi B, Stewart D, Levan M, Massie A, Gentry S, Segev D. ChatGPT Solving Complex Kidney Transplant Cases: A Comparative Study With Human Respondents. Clinical Transplantation 2024;38(10) View
  9. Tudino G, Qin Y. A corpus-driven comparative analysis of AI in academic discourse: Investigating ChatGPT-generated academic texts in social sciences. Lingua 2024;312:103838 View
  10. Zare S, Vafaeian S, Amini M, Farhadi K, Vali M, Golestani A. Comparing the performance of ChatGPT-3.5-Turbo, ChatGPT-4, and Google Bard with Iranian students in pre-internship comprehensive exams. Scientific Reports 2024;14(1) View
  11. Agaronnik N, Davis J, Manz C, Tulsky J, Lindvall C. Large Language Models to Identify Advance Care Planning in Patients With Advanced Cancer. Journal of Pain and Symptom Management 2025;69(3):243 View
  12. Dornburg A, Davin K. ChatGPT in foreign language lesson plan creation: Trends, variability, and historical biases. ReCALL 2025;37(3):332 View
  13. Hamilton Z, Aseem A, Chen Z, Naffakh N, Reizine N, Weinberg F, Jain S, Kessler L, Gadi V, Bun C, Nguyen R. Comparative Analysis of Generative Pre-Trained Transformer Models in Oncogene-Driven Non–Small Cell Lung Cancer: Introducing the Generative Artificial Intelligence Performance Score. JCO Clinical Cancer Informatics 2024;(8) View
  14. Jackson V, Vasilescu B, Russo D, Ralph P, Prikladnicki R, Izadi M, D’Angelo S, Inman S, Andrade A, van der Hoek A. The Impact of Generative AI on Creativity in Software Development: A Research Agenda. ACM Transactions on Software Engineering and Methodology 2025;34(5):1 View
  15. Flanagan C, Trang K, Nacario J, Schneider P, Gasper W, Conte M, Wick E, Conway A. Large language models can accurately populate Vascular Quality Initiative procedural databases using narrative operative reports. Journal of Vascular Surgery 2025;81(4):973 View
  16. Gielens E, Sowula J, Leifeld P. Goodbye human annotators? Content analysis of social policy debates using ChatGPT. Journal of Social Policy 2025:1 View
  17. Zhong C, Luo X, Tan M, Chi J, Guo B, Tang J, Guo Z, Deng S, Zhang Y, Wu Y. Digital Health Interventions to Improve Mental Health in Patients With Cancer: Umbrella Review. Journal of Medical Internet Research 2025;27:e69621 View
  18. Kerr W, McFarlane K, Pucci G, Carns D, Israel A, Vighetti L, Pennell P, Stern J, Xia Z, Wang Y. Supervised machine learning compared to large language models for identifying functional seizures from medical records. Epilepsia 2025;66(4):1155 View
  19. Mane P. Accuracy and creativity analysis of ChatGPT in quantitative aptitude. The International Journal of Information and Learning Technology 2025;42(2):224 View
  20. Aster A, Ragaller S, Raupach T, Marx A. ChatGPT as a Virtual Patient: Written Empathic Expressions During Medical History Taking. Medical Science Educator 2025;35(3):1513 View
  21. Yang Y, Ma L. Artificial intelligence in qualitative analysis: a practical guide and reflections based on results from using GPT to analyze interview data in a substance use program. Quality & Quantity 2025;59(3):2511 View
  22. Fung M, Tang E, Wu T, Luk Y, Au I, Liu X, Lee V, Wong C, Wei Z, Cheng W, Tai I, Ho J, Wong J, Lang B, Leung K, Wong Z, Wu J, Wong C. Developing a named entity framework for thyroid cancer staging and risk level classification using large language models. npj Digital Medicine 2025;8(1) View
  23. Zhang Y, Fang J, Luo X, Lindsay D, Madre N, Paredes J, Penna A, Melley E, Garcia T. Exploring the efficacy of ChatGPT in understanding and identifying intimate partner violence. Family Relations 2025;74(3):1233 View
  24. Agaronnik N, Davis J, Manz C, Tulsky J, Lindvall C. Feasibility Study for Using Large Language Models to Identify Goals-of-Care Documentation at Scale in Patients With Advanced Cancer. JCO Oncology Practice 2025 View
  25. Yeung A, Hammerle F, Behrens S, Matin M, Mickael M, Litvinova O, Parvanov E, Kletecka-Pulker M, Atanasov A. Online Information About Side Effects and Safety Concerns of Semaglutide: Mixed Methods Study of YouTube Videos. JMIR Infodemiology 2025;5:e59767 View
  26. Grilo A, Marques C, Corte-Real M, Carolino E, Caetano M. Assessing the Quality and Reliability of ChatGPT’s Responses to Radiotherapy-Related Patient Queries: Comparative Study With GPT-3.5 and GPT-4. JMIR Cancer 2025;11:e63677 View
  27. Abdurahman S, Salkhordeh Ziabari A, Moore A, Bartels D, Dehghani M. A Primer for Evaluating Large Language Models in Social-Science Research. Advances in Methods and Practices in Psychological Science 2025;8(2) View
  28. Peters U, Chin-Yee B. Generalization bias in large language model summarization of scientific research. Royal Society Open Science 2025;12(4) View
  29. Eymann V, Lachmann T, Czernochowski D. When ChatGPT Writes Your Research Proposal: Scientific Creativity in the Age of Generative AI. Journal of Intelligence 2025;13(5):55 View
  30. Yu Q, Que T, Cushing L, Pierce G, Shen K, Kejriwal M, Yao Y, Zhu Y. Equity and reliability of public electric vehicle charging stations in the United States. Nature Communications 2025;16(1) View
  31. Tripathi S, Alkhulaifat D, Lyo S, Sukumaran R, Li B, Acharya V, McBeth R, Cook T. A Hitchhiker's Guide to Good Prompting Practices for Large Language Models in Radiology. Journal of the American College of Radiology 2025;22(7):841 View
  32. Rudko I, Bashirpour Bonab A. ChatGPT is incredible (at being average). Ethics and Information Technology 2025;27(3) View
  33. Jukiewicz M. How generative artificial intelligence transforms teaching and influences student wellbeing in future education. Frontiers in Education 2025;10 View
  34. Kliem P, Fisch U, Baumann S, Berger S, Amacher S, Hunziker S, Sutter R. The impact of prompting on ChatGPT’s adherence to status epilepticus treatment guidelines. Scientific Reports 2025;15(1) View
  35. Bilon X. Can large language models support health literacy? Examining sociodemographic biases in ChatGPT’s representation of HIV knowledge. Journal of HIV/AIDS & Social Services 2025:1 View
  36. Ignjatović A, Anđelković Apostolović M, Stevanović L, Radovanović P, Topalović M, Filipović T, Otašević S. ChatGPT’s progress over time: A longitudinal enhancing biostatistical problem-solving in medical education. Health Informatics Journal 2025;31(3) View
  37. Mehta S, Paul S, Awiti E, Young S, Zulaika G, Otieno F, Phillips-Howard P, Mason L, Bhaumik R. Evaluation of large language models within GenAI in qualitative research. Scientific Reports 2025;15(1) View
  38. Jarrett P, Hill J, Howell M, Grabow Moore K, Thoppil J, Vargas Ortiz L, Parnell S, Courtney D, McDonald S, Diercks D, Jamieson A, Cao D. Piloting Temperature-Driven Variability in Emergency Diagnostic Accuracy Using a Leading Large Language Model. Cureus 2025 View
  39. Pushpanathan K, Zou M, Srinivasan S, Tham Y. Reply. Ophthalmology Science 2026;6(1):100969 View
  40. Wu Y, Hu P, Wang D. The AI Annotator: Large Language Models’ Potential in Scoring Sustainability Reports. Systems 2025;13(10):899 View
  41. Flanagan C, Gerstley L, Okuhn S, McLenon M, Lancaster E, Hull M, Bulbule M, Sivamurthy N, Chang R. Large language models accurately extract aortic information from abdominal imaging reports in a large, real-world database. Journal of Vascular Surgery 2025 View
  42. Thomas J, Elyoseph Z, Kuchinke L, Meinlschmidt G. Large language model performance versus human expert ratings in automated suicide risk assessment. Scientific Reports 2025;15(1) View
  43. Zeng J, Qi W, Shen S, Liu X, Li S, Wang B, Dong C, Zhu X, Shi Y, Lou X, Wang B, Yao J, Jiang G, Zhang Q, Cao S. Embracing the Future of Medical Education With Large Language Model–Based Virtual Patients: Scoping Review. Journal of Medical Internet Research 2025;27:e79091 View
  44. Sciurti A, Migliara G, Siena L, Isonne C, De Blasiis M, Sinopoli A, Iera J, Marzuillo C, De Vito C, Villari P, Baccolini V. Compact large language models for title and abstract screening in systematic reviews: An assessment of feasibility, accuracy, and workload reduction. Research Synthesis Methods 2025:1 View
  45. Pohlmann P, Glienke M, Sandkamp R, Gratzke C, Schmal H, Schoeb D, Fuchs A. Assessing the Efficacy of Ortho GPT: A Comparative Study with Medical Students and General LLMs on Orthopedic Examination Questions. Bioengineering 2025;12(12):1290 View
  46. Kariv D, Attar I, Haber Y, Elyoseph Z. AI-simulated entrepreneurship under uncertainty: forecasting university-driven capability evolution. The Journal of Technology Transfer 2025 View
  47. Tripathi M, Liapis I, Sanghera J, Annesi C, Landrum A, Kumar S, Bhatia S, Fonseca A. Leveraging Large Language Models to Automate Scoping Reviews: A Case Study in Treatment Options for Pancreatic Cancer. The American Journal of Surgery 2025:116764 View
  48. Nnanna P, Amujo O, Ezenkwu C, Ibeke E. Leveraging LLMs for User Rating Prediction from Textual Reviews: A Hospitality Data Annotation Case Study. Information 2025;16(12):1059 View

Books/Policy Documents

  1. Pears M, Konstantinidis S. Disruptive Technologies in Education and Workforce Development. View
  2. Cosentino C, Gündüz-Cüre M, Marozzo F, Öztürk-Birim Ş. Discovery Science. View
  3. Laneve C, Spanò A, Ressi D, Rossi S, Bugliesi M. Formal Techniques for Distributed Objects, Components, and Systems. View
  4. Sivakumar M, Imran A, Kastrati Z, Soylu A, Kastrati M. Proceedings of the Future Technologies Conference (FTC) 2025, Volume 4. View

Conference Proceedings

  1. Baumartz D, Konca M, Mehler A, Schrottenbacher P, Braunheim D. Proceedings of the 35th ACM Conference on Hypertext and Social Media. Measuring Group Creativity of Dialogic Interaction Systems by Means of Remote Entailment Analysis View
  2. Gourabathina A, Gerych W, Pan E, Ghassemi M. Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency. The Medium is the Message: How Non-Clinical Information Shapes Clinical Decisions in LLMs View