Journals / Celal Bayar Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi / 2026 / Volume: 11 Issue: 1

ChatGPT and its use in Healthcare

ChatGPT ve Sağlık Bilimlerinde Kullanımı

Alper Eriç(MARMARA ÜNİVERSİTESİ, TIP FAKÜLTESİ)0000-0001-8619-7980
Emrah Gökay Özgür(MARMARA ÜNİVERSİTESİ, TIP FAKÜLTESİ)0000-0002-3966-4184
Ömer Faruk Asker(MARMARA ÜNİVERSİTESİ, TIP FAKÜLTESİ)0009-0000-5561-0277
Nural Bekiroğlu(MARMARA ÜNİVERSİTESİ, TIP FAKÜLTESİ)0000-0001-6471-6612
Pages
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Publication Date
2024-03-27
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This article discusses chatbots, natural language processing, computational linguistics, ChatGPT, and its use in the medical field.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Chat Generative Pre-Trained Transformer (ChatGPT) is one of the largest language models ever developed by OpenAI.
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Key Findings & Data:Just five days after its release, it reached one million users, and within two months, it became the fastest-growing consumer application in history, reaching 100 million monthly active users, causing great excitement.
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Conclusion & Impact:This article discusses chatbots, natural language processing, computational linguistics, ChatGPT, and its use in the medical field.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:ChatGPT · Artificial Intelligence in Healthcare · Chatbot

Abstract

Chat Generative Pre-Trained Transformer (ChatGPT) is one of the largest language models ever developed by OpenAI. Just five days after its release, it reached one million users, and within two months, it became the fastest-growing consumer application in history, reaching 100 million monthly active users, causing great excitement. Unlike similar language models, ChatGPT can answer consecutive questions, accept errors in its responses when prompted, understand and respond in different languages, and reject inappropriate questions. There have been discussions on how ChatGPT can be used in the healthcare field, particularly in medicine, and many publications have been made on this topic. This article discusses chatbots, natural language processing, computational linguistics, ChatGPT, and its use in the medical field.

Özet

Chat Generative Pre-Trained Transformer (ChatGPT), OpenAI tarafından geliştirilen şimdiye kadar yapılmış en büyük dil modellerinden biridir. Kullanıma açılmasından beş gün sonra bir milyon kullanıcıya ulaşmış, sadece iki ay sonra ise aylık 100 milyon aktif kullanıcıya ulaşarak tarihin en hızlı büyüyen tüketici uygulaması haline gelmiş ve büyük bir heyecana yol açmıştır. ChatGPT’nin, benzer dil modellerinden farklı olarak birbirini takip eden soruları yanıtlayabildiği, uyarıldığında yanıtlarındaki hataları kabul edip düzenlemeler yapabildiği, farklı dilleri anlayıp bu dillerde cevaplar verebildiği ve yöneltilen sorulardan uygun olmayanları yanıtlamayı reddedebildiği görülmektedir. ChatGPT’nin sağlık alanında özellikle tıpta nasıl kullanılabileceği ve neler yapabildiği tartışılmış ve bu konuda birçok yayın yapılmıştır. Bu makale chatbotlar, doğal dil işleme, hesaplamalı dilbilim, ChatGPT ve tıp alanındaki kullanımını konu almaktadır.

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Cite This Article

Eriç, A., Özgür, E. G., Asker, Ö. F., Bekiroğlu, N. (2024). ChatGPT and its use in Healthcare. Celal Bayar Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi, Volume: 11 Issue: 1. https://doi.org/10.34087/cbusbed.1262811

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References (41)

  1. Kung, T.H, Cheatham, M, Medenilla, A, Sillos, C, De Leon, L, Elepaño, C, vd., Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models, PLOS Digital Health, 2023, 2(2), e0000198.
  2. Kurian, N, Cherian, J, Sudharson, N. et al. AI is now everywhere, British Dental Journal, 2023, 234, 72-72.
  3. The Guardian, ChatGPT reaches 100 million users two months after launch. https://www.theguardian.com/technology/2023/feb/02/chatgpt-100-million-users-open-ai-fastest-growing-app
  4. Reuters, ChatGPT sets record for fastest-growing user base - analyst note. https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/
  5. Taecharungroj, V, “What Can ChatGPT Do?” Analyzing Early Reactions to the Innovative AI Chatbot on Twitter, Big Data and Cognitive Computing, 2023, 7(1), 35.
  6. Shen, Y, Heacock, L, Elias, J, Hentel, K.D, Reig, B, Shih, G, vd., ChatGPT and Other Large Language Models Are Double-edged Swords, Radiological Society of North America (RSNA), 2023.
  7. Xu, L, Sanders, L, Li, K, Chow, J.C.L, Chatbot for Health Care and Oncology Applications Using Artificial Intelligence and Machine Learning, JMIR Cancer, 2021, 7, e27850.
  8. Sansonnet, J.P, Leray, D, Martin, J.C, Architecture of a Framework for Generic Assisting Conversational Agents, Intelligent Virtual Agents, 2006, 145-56.
  9. Pinar Saygin, A, Cicekli, I, Akman, V. C, Minds and Machines, Springer Science and Business Media LLC, 2000, 10(4), 463-518.
  10. Turing, A.M, Computing Machinery and Intelligence, Oxford University Press (OUP), 1950, 59(236), 433-60.
  11. Adamopoulou, E, Moussiades, L, Chatbots: History, technology, and applications, Machine Learning with Applications, 2020, 2, 100006.
  12. Weizenbaum, J, ELIZA- a computer program for the study of natural language communication between man and machine, Association for Computing Machinery (ACM), 1966, 9, 36-45.
  13. Klopfenstein, L.C, Delpriori, S., Malatini, S, Bogliolo, A, The Rise of Bots: A Survey of Conversational Interfaces, Patterns, and Paradigms, Proceedings of the 2017 Conference on Designing Interactive Systems. ACM, 2017.
  14. Wallace, R.S, The Anatomy of A.L.I.C.E. In: Parsing the Turing Test, Springer Netherlands, 2007. s. 181-210.
  15. Aydın, Ö, Karaarslan, E, Is ChatGPT Leading Generative AI? What is Beyond Expectations?, SSRN Electronic Journal, 2023.
  16. Locke, S, Bashall, A, Al-Adely, S, Moore, J, Wilson, A, Kitchen, G.B, Natural language processing in medicine: A review, Trends in Anaesthesia and Critical Care, 2021, 38, s. 4-9.
  17. Biswas, S, ChatGPT and the Future of Medical Writing, Radiological Society of North America (RSNA), 2023.
  18. Clark, A, Fox, C, Lappin, S, The Handbook of Computational Linguistics and Natural Language Processing, John Wiley & Sons, 2012, pp 1-2;
  19. Kamath, U, Liu, J, Whitaker, J, Deep Learning for NLP and Speech Recognition,. Springer International Publishing, 2019, 87-91
  20. Deng, L, Liu, Y, Deep Learning in Natural Language Processing. In: A Joint Introduction to Natural Language Processing and to Deep Learning, Springer Singapore, 2018, pp. 1-22
  21. Vaswani, A, Shazeer, N, Parmar, N, Uszkoreit, J, Jones, L, Gomez, A, vd., Attention is all you need. Advances in neural information processing systems, 30.
  22. nvidia.developer, Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, the World’s Largest and Most Powerful Generative Language Model,https://developer.nvidia.com/blog/using-deepspeed-and-megatron-to-train-megatron-turing-nlg-530b-the-worlds-largest-and-most-powerful-generative-language-model/
  23. Gillioz, A, Casas, J, Mugellini, E, Khaled, O.A, Overview of the Transformer-based Models for NLP Tasks, Proceedings of the 2020 Federated Conference on Computer Science and Information Systems, IEEE, 2020.
  24. OpenAI, Introducing ChatGPT, https://openai.com/blog/chatgpt/
  25. Matsuo, Y, LeCun, Y, Sahani, M, Precup, D, Silver, D, Sugiyama, M, vd. Deep learning, reinforcement learning, and world model, Neural Networks, 2022, 152, 267-75.
  26. Jonsson, A, Deep Reinforcement Learning in Medicine, Kidney Diseases (S. Karger AG), 2018, 5, 18–22.
  27. Devlin, J, Chang, M. W, Lee, K, Toutanova, K, Bert: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of naacL-HLT, 2019, pp. 4171-4186.
  28. OpenAI, Proximal Policy Optimization, https://openai.com/blog/openai-baselines-ppo/
  29. van Dis, E.A.M, Bollen, J, Zuidema, W, van Rooij, R, Bockting, C.L, ChatGPT: five priorities for research, Nature Springer Science and Business Media LLC, 2023, 614, 224-6.
  30. Patel, S.B, Lam, K, ChatGPT: the future of discharge summaries?, The Lancet Digital Health, 2023, 5, e107-8.
  31. Aljanabi, M, ChatGPT, ChatGPT: Future Directions and Open possibilities, Mesopotamian Journal of Cyber Security. Mesopotamian Academic Press; 2023, 16-7.
  32. Khan, R.A, Jawaid, M, Khan, A.R, Sajjad, M, ChatGPT - Reshaping medical education and clinical management, Pakistan Journal of Medical Sciences, 2023, 39.
  33. Wang, X, Gong, Z, Wang, G, Jia, J, Xu, Y, Zhao, J, vd. ChatGPT Performs on the Chinese National Medical Licensing Examination, Research Square Platform LLC, 2023.
  34. Gilson, A, Safranek, C.W, Huang, T, Socrates, V, Chi, L, Taylor, R.A, vd. How Does ChatGPT Perform on the United States Medical Licensing Examination? The Implications of Large Language Models for Medical Education and Knowledge Assessment, JMIR Medical Education, 2023, 9, e45312.
  35. Mbakwe, A.B, Lourentzou, I, Celi, L.A, Mechanic, O.J, Dagan, A, ChatGPT passing USMLE shines a spotlight on the flaws of medical education, PLOS Digital Health, 2023, 2, e0000205.
  36. Sharma, G, Thakur, A, ChatGPT in Drug Discovery, American Chemical Society (ACS), 2023.
  37. Sinha, R.K, Deb Roy, A, Kumar, N, Mondal, H, Applicability of ChatGPT in Assisting to Solve Higher Order Problems in Pathology, Cureus, 2023.
  38. Bhattacharya, K, Bhattacharya, A.S, Bhattacharya, N, Yagnik, V.D, Garg, P, Kumar, S, ChatGPT in Surgical Practice—a New Kid on the Block, Indian Journal of Surgery, 2023.
  39. Howard, A, Hope, W, Gerada, A, ChatGPT and antimicrobial advice: the end of the consulting infection doctor?, The Lancet Infectious Diseases, 2023.
  40. Kung, T.H, Cheatham, M, Medenilla, A, Sillos, C, De Leon, L, Elepaño, C, vd., Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models, PLOS Digital Health, 2023, 2(2), e0000198.
  41. Wallace, R.S, The Anatomy of A.L.I.C.E. In: Parsing the Turing Test, Springer Netherlands, 2007. s. 181-210.