A comprehensive survey of ChatGPT: Advancements, applications, prospects, and challenges
Open accessAbstract
Large Language Models (LLMs) especially when combined with Generative Pre-trained Transformers (GPT) represent a groundbreaking in natural language processing. In particular, ChatGPT, a state-of-the-art conversational language model with a user-friendly interface, has garnered substantial attention owing to its remarkable capability for generating human-like responses across a variety of conversational scenarios. This survey offers an overview of ChatGPT, delving into its inception, evolution, and key technology. We summarize the fundamental principles that underpin ChatGPT, encompassing its introduction in conjunction with GPT and LLMs. We also highlight the specific characteristics of GPT models with details of their impressive language understanding and generation capabilities. We then summarize applications of ChatGPT in a few representative domains. In parallel to the many advantages that ChatGPT can provide, we discuss the limitations and challenges along with potential mitigation strategies. Despite various controversial arguments and ethical concerns, ChatGPT has drawn significant attention from research industries and academia in a very short period. The survey concludes with an envision of promising avenues for future research in the field of ChatGPT. It is worth noting that knowing and addressing the challenges faced by ChatGPT will mount the way for more reliable and trustworthy conversational agents in the years to come.
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Most prior research in this field speculates on high-level concerns such as inaccuracy and real-world impacts, but rarely articulates concrete criteria for when and why LLMs should or should not provide professional advice to users.
“Most prior research in this field speculates on high-level concerns such as inaccuracy and real-world impacts [43, 44, 54, 86, 93]. However, these studies rarely articulate concrete criteria for when and why LLMs should or should not provide professional advice to users.”
From (A)I Am Not a Lawyer, But...: Engaging Legal Experts towards Responsible LLM Policies for Legal Advice (2024) · cites this paper as [54]
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“If the training dataset for a particular domain lacks depth or breadth, the responses in that domain might not meet the desired standards [73].”
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“AI systems learn from the data they are fed, and if these data include biases, the AI is likely to replicate and even amplify these biases in its outputs [31].”
ChatGPT in medicine: prospects and challenges: a review article
Tan, S., Xin, X., & Wu, D. (2024) · International Journal of Surgery · doi:10.1097/js9.0000000000001312 · Cited by 128 · see citing works
“ChatGPT can be incorporated into the present education platform as a virtual tutor, creating a more engaging and impactful learning environment tailored to student ’ s individual learning pace and preferences [29] .”
BackgroundChatGPT: perspectives from human–computer interaction and psychology
Liu, J. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2024.1418869 · Cited by 99 · see citing works
Cheong, I., Xia, K., Feng, K. J. K., Chen, Q. Z., & Zhang, A. X. (2024) · The 2024 ACM Conference on Fairness Accountability and Transparency · doi:10.1145/3630106.3659048 · Cited by 91 · see citing works
Simon, B. D., Ozyoruk, K. B., Gelikman, D. G., Harmon, S. A., & Türkbey, B. (2024) · Diagnostic and Interventional Radiology · doi:10.4274/dir.2024.242631 · Cited by 73 · see citing works
“25,26 .”
Reliability of ChatGPT in automated essay scoring for dental undergraduate examinations
Quah, B., Zheng, L., Sng, T. J. H., Yong, C. W., & Islam, I. (2024) · BMC Medical Education · doi:10.1186/s12909-024-05881-6 · Cited by 81 · see citing works
“Second, prompt engineering is a critical step in producing the desired outcome from ChatGPT [27].”
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Large Language Model-Powered Automated Assessment: A Systematic Review
Emirtekin, E. (2025) · Applied Sciences · doi:10.3390/app15105683 · Cited by 87 · see citing works
Linkon, A. A., Shaima, M., Sarker, M. S. U., Badruddowza, B., Nabi, N., Rana, M. N. U., Ghosh, S. K., Esa, H., & Chowdhury, F. R. (2024) · Journal of Computer Science and Technology Studies · doi:10.32996/jcsts.2024.6.1.26 · Cited by 67 · see citing works
Can ChatGPT evaluate research quality?
Thelwall, M. (2024) · Journal of Data and Information Science · doi:10.2478/jdis-2024-0013 · Cited by 68 · see citing works
“More generally, the results of this study also confirm prior observations that ChatGPT can generate output that is plausible but inaccurate (Nazir & Wang, 2023).”
Li, Y., Zhao, J., Li, M., Dang, Y., Yu, E. Y., Li, J., Sun, Z., Hussein, U., Wen, J., Abdelhameed, A. M., et al. (2024) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocae129 · Cited by 62 · see citing works
Ma, W., Wen-jing, M., Hu, Y., & Xinyu, B. I. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13128-6 · Cited by 71 · see citing works
“Moreover, with the continuous evolution of natural language processing technology, these AI-based chatbots have been able to guide students to participate in in-depth conversations, further promoting their deepening of understanding and knowledge system construction (Nazir & Wang, 2023).”
Taani, O., & Alabidi, S. (2024) · International Journal of Mathematical Education in Science and Technology · doi:10.1080/0020739x.2024.2357341 · Cited by 71 · see citing works
“Context is vital for ChatGPT to process information and generate responses accordingly (Ansari et al., 2024; Kondurkar et al., 2024; Min et al.,2023; Nazir & Wang, 2023).”
Strika, Z., Petković, K., Likić, R., & Batenburg, R. S. (2024) · Postgraduate Medical Journal · doi:10.1093/postmj/qgae122 · Cited by 59 · see citing works
Chain-of-Thought in Neural Code Generation: From and for Lightweight Language Models
Yang, G., Zhou, Y., Chen, X., Zhang, X., Zhuo, T. Y., & Chen, T. (2024) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2024.3440503 · Cited by 56 · see citing works
“[5], [6].”
Innovation and application of Large Language Models (LLMs) in dentistry – a scoping review
Umer, F., Batool, I., & Naved, N. (2024) · BDJ Open · doi:10.1038/s41405-024-00277-6 · Cited by 57 · see citing works
Nia, M. F., Ahmadi, M., & Irankhah, E. (2025) · Frontiers in Dental Medicine · doi:10.3389/fdmed.2024.1456208 · Cited by 60 · see citing works
Fortuna, A., Prasetya, F., Samala, A. D., Rawas, S., Criollo-C, S., Kaya, D., Raihan, M. F. M., Andriani, W., Safitri, D., & Nabawi, R. A. (2025) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2025.102114 · Cited by 82 · see citing works
Qin, H., Zhu, Y., Jiang, Y., Luo, S., & Huang, C. (2024) · Technology in Society · doi:10.1016/j.techsoc.2024.102726 · Cited by 51 · see citing works
Ethics of AI in healthcare: a scoping review demonstrating applicability of a foundational framework
Gorelik, A. J., Li, M., Hahne, J., Wang, J., Ren, Y., Yang, L., Zhang, X., Liu, X., Wang, X., Bogdan, R., et al. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1662642 · Cited by 48 · see citing works
How reliable is the artificial intelligence product large language model ChatGPT in orthodontics?
Demirsoy, K. K., Büyük, S. K., & Bicer, T. (2024) · The Angle Orthodontist · doi:10.2319/031224-207.1 · Cited by 44 · see citing works
Tuan, N. T., Moore, P. T., Thanh, D. H. V., & Pham, H. V. (2024) · Applied Sciences · doi:10.3390/app14073036 · Cited by 49 · see citing works
“The latest versions of ChatGPT models and Google’s BARD [13,14] have been used in the evaluation of reasoning domains such as deductive, inductive, and question-answering tasks.”
BackgroundMethodAlier, M., Pereira, J., García‐Peñalvo, F. J., Guerrero, M. J. C., & Cabré, J. (2024) · Computer Standards & Interfaces · doi:10.1016/j.csi.2024.103940 · Cited by 76 · see citing works
Performance of large language models in oral and maxillofacial surgery examinations
Quah, B., Yong, C. W., Lai, C. W. M., & Islam, I. (2024) · International Journal of Oral and Maxillofacial Surgery · doi:10.1016/j.ijom.2024.06.003 · Cited by 40 · see citing works
University students’ perceptions of using generative AI in translation practices
Zhang, W., Li, A. W., & Wu, C. (2025) · Instructional Science · doi:10.1007/s11251-025-09705-y · Cited by 60 · see citing works
“…efficiency by providing students with the translated texts immediately and it saves the time spent on pre-translation resources, which means GenAI tools are time-saving and have the potential to offer effective support to facilitate the work efficiency of translators (Nazir & Wang, 2023 ).”
Anica-Popa, I., Vrîncianu, M., Anica-Popa, L.-E., Cișmașu, I.-D., & Tudor, C. T. L. G. (2024) · Electronics · doi:10.3390/electronics13132621 · Cited by 52 · see citing works
Barr, A. A., Quan, J., Guo, E., & Sezgın, E. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1533508 · Cited by 38 · see citing works
Current applications and future potential of C hat GPT in radiology: A systematic review
Temperley, H. C., O’Sullivan, N. J., Curtain, B. M. M., Corr, A., Meaney, J. F., Kelly, M. E., & Brennan, I. M. (2024) · Journal of Medical Imaging and Radiation Oncology · doi:10.1111/1754-9485.13621 · Cited by 37 · see citing works
“5 The potential applications of GPT-based models in radiology are vast and offer exciting prospects for the future.”
BackgroundHuang, T. Y., Safranek, C. W., Socrates, V., Chartash, D., Wright, D., Dilip, M., Sangal, R. B., & Taylor, R. A. (2024) · Journal of Medical Internet Research · doi:10.2196/60336 · Cited by 37 · see citing works
“…could look toward expanding the scope of the use of LLMs in discharge instructions, such as integrating multicultural and multilingual personalization into discharge instructions as well as expanding the amount of teaching and patient education embedded into the discharge instructions [41,42].”
Al-Abri, A. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13484-x · Cited by 44 · see citing works
“This aspect supports modern learners’ increasingly diverse schedules, emphasizing the trans-formative potential of constant access to educational support (Nazir & Wang, 2023).”
InfluentialAn Empirical Study on Challenges for LLM Application Developers
Chen, X., Gao, C., Chen, C., Zhang, G., & Liu, Y. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3715007 · Cited by 47 · see citing works
Looi, C., & Jia, F. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13369-z · Cited by 42 · see citing works
“Currently, ChatGPT lacks the ability to create persistent and evolving models of individual learners that extend beyond a single session (Nazir & Wang, 2023).”
Waga, A., Benhlima, S., Bekri, A., Abdouni, J., & Saber, F. Z. (2025) · Journal of King Saud University - Computer and Information Sciences · doi:10.1007/s44443-025-00216-x · Cited by 39 · see citing works
Kavitha, K., Joshith, V. P., & Sharma, S. (2024) · E-Learning and Digital Media · doi:10.1177/20427530241259099 · Cited by 32 · see citing works
“Further, with its capability to generate human-like responses and engage in lively conversations (Nazir and Wang, 2023), ChatGPT holds promise as a tool that aligns with Gen Z ’ s digital pro fi ciency and communication preferences.”
Artificial intelligence and ChatGPT are fostering knowledge sharing, ethics, academia and libraries
Zeb, A., Rehman, F. U., Othayman, M. B., & Rabnawaz, M. (2024) · International Journal of Information and Learning Technology · doi:10.1108/ijilt-03-2024-0046 · Cited by 40 · see citing works
Alyasiri, O. M., Salisu, S., Younis, H., Salman, A. M., Sahib, T. M., Akhtom, D., & Hayder, I. M. (2024) · Journal of Stomatology Oral and Maxillofacial Surgery · doi:10.1016/j.jormas.2024.101842 · Cited by 31 · see citing works
Yang, Q., & Lee, Y. (2024) · Journal of risk and financial management · doi:10.3390/jrfm17100470 · Cited by 39 · see citing works
A hybrid framework for creating artificial intelligence-augmented systematic literature reviews
Malik, F. S., & Terzidis, O. (2026) · Management Review Quarterly · doi:10.1007/s11301-025-00522-8 · Cited by 28 · see citing works
“…like GPT-4 offer robust capabilities, special - ized models such as PubMedBERT or ClinicalBERT demonstrate superior perfor - mance in niche areas like medical literature reviews (Alavi et al. 2024; Alshami et al. 2023; Benbya et al. 2024; Dwivedi et al. 2023; Nazir and Wang 2023; O’Connor 2022).”
Large Language Models for Mobility Analysis in Transportation Systems: A Survey on Forecasting Tasks
Zhang, Z., Sun, Y., Wang, Z., Nie, Y., Ma, X., Li, R., Sun, P., & Ban, X. J. (2025) · Transportation Research Record Journal of the Transportation Research Board · doi:10.1177/03611981251367699 · Cited by 28 · see citing works
“Forecasting the mobility of vehicles and pedestrians is crucial for planning and optimizing transportation systems that enable the movement of people and goods within and across different areas ( 1–3 ).”
Self-citationFiletti, S., Fenza, G., & Gallo, A. (2024) · Endocrine · doi:10.1007/s12020-024-03977-z · Cited by 32 · see citing works
“The introduction of GPT-4 [19] and the integration of plugins have signi fi cantly expanded ChatGPT ’ s capabilities and versatility.”
Zhou, J., & Camba, J. D. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.127520 · Cited by 27 · see citing works
Wang, C., Wang, Y., & Zou, B. (2024) · Journal of Language Teaching · doi:10.54475/jlt.2024.004 · Cited by 25 · see citing works
“Additionally, they can assist students in understanding challenging content through translation (Nazir & Wang, 2023).”
BackgroundXu, S., Chen, P., & Zhang, G. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e39845 · Cited by 24 · see citing works
Surprising gender biases in GPT
Fulgu, R. A., & Capraro, V. (2024) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2024.100533 · Cited by 24 · see citing works
A systematic review of AI-driven business models for advancing Sustainable Development Goals
Khan, M. A., Rahman, A., Mahmud, F. U., Bishnu, K. K., Ahmed, M., Mridha, M. F., & Aung, Z. (2025) · Array · doi:10.1016/j.array.2025.100539 · Cited by 22 · see citing works
Carik, B., Izaac, V. V., Ding, X., Scarpa, A., & Rho, E. H. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714287 · Cited by 21 · see citing works
Lu, R.-S., Lin, H.-C. K., Yang, Y.-C., & Chen, Y.-P. (2024) · Sustainability · doi:10.3390/su162411304 · Cited by 24 · see citing works
Shahin, M., & Simjoo, M. (2025) · International Journal of Hydrogen Energy · doi:10.1016/j.ijhydene.2025.01.066 · Cited by 20 · see citing works
Wang, X.-M., Huang, X.-T., & Zhou, W.-Q. (2024) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2024.101658 · Cited by 27 · see citing works
A review of ChatGPT in medical education: exploring advantages and limitations
Cheng, Y., & Zhu, L. (2025) · International Journal of Surgery · doi:10.1097/js9.0000000000002505 · Cited by 24 · see citing works
Wang, S., Ouyang, Q., & Wang, B. (2024) · Research Square · doi:10.21203/rs.3.rs-3987793/v1 · Cited by 20 · see citing works
ChatGPT and generation 'Z': a study on the usage rates of ChatGPT
Babu, M. A., Yusuf, K. M., Eni, L. N., Jaman, S. M. S., & Sharmin, M. R. (2024) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2024.101163 · Cited by 19 · see citing works
A survey analysis of the adoption of large language models among pathologists
Laohawetwanit, T., Pinto, D. G., & Bychkov, A. (2024) · American Journal of Clinical Pathology · doi:10.1093/ajcp/aqae093 · Cited by 16 · see citing works
The Role of ChatGPT in Dermatology Diagnostics
Khamaysi, Z., Awwad, M., Jiryis, B., Bathish, N., & Shapiro, J. (2025) · Diagnostics · doi:10.3390/diagnostics15121529 · Cited by 13 · see citing works
“…datasets and influential in the constructive identification of features of skin lesions, could do much better with the input of ChatGPT for its natural processing of language in preparation for interpretive summaries or comments that could provide human interpreters with a little help [28,29].”
Quantum artificial intelligence: A survey
Acampora, G., Chiatto, A., Schiattarella, R., & Vitiello, A. (2025) · Computer Science Review · doi:10.1016/j.cosrev.2025.100807 · Cited by 14 · see citing works
Doctoral Programme in Education Science Universitas Pendidikan Ganesha, S., & Turmuzi, M. (2024) · International Journal of Information and Education Technology · doi:10.18178/ijiet.2024.14.5.2097 · Cited by 17 · see citing works
“These findings supported the research of Sakirin and Said [61], Nazir and Wang [62], which found that ChatGPT’s user-friendliness is yet another fantastic feature.”
ResultUndergraduate Nursing Students’ Perspectives on Artificial Intelligence in Academia
Lam, M., Adhami, N., Du, O., Huntley, R., Abdulai, A.-F., Yi Wong, K. L., & Hung, L. (2025) · Canadian Journal of Nursing Research · doi:10.1177/08445621251347025 · Cited by 13 · see citing works
“…and are integrated into healthcare technologies, the adoption of such tools into nursing education curriculums may play an important role in fostering student competency and familiarity with AI technologies in nursing practice (Labrague et al., 2023; Nazir & Wang, 2023; Sun & Hoelscher, 2023).”
InfluentialLeveraging Generative AI for sustainable supply chain: adoption challenges and strategic insights
Maghroor, H. R., Madanchi, F., & O’Neal, T. (2025) · Production Planning & Control · doi:10.1080/09537287.2025.2561967 · Cited by 15 · see citing works
Charge-triggered switching mechanism in selenium selector enabling ultralow leakage current
Sun, Y., Gotoh, T., Zhao, J., Zhang, M., Shi, S., Zhang, H., Liu, Z., Shen, J., Dronskowski, R., Song, Z., et al. (2026) · Nature Materials · doi:10.1038/s41563-026-02499-5 · Cited by 13 · see citing works
ChatGPT-based biological and psychological data imputation
Nazir, A., Cheema, M. N., & Wang, Z. (2023) · Meta-Radiology · doi:10.1016/j.metrad.2023.100034 · Cited by 13 · see citing works
Self-citationGenerative AI for Secure User Interface (UI) Design
Sindiramutty, S. R., Prabagaran, K. R. V., Akbar, R., Hussain, M., & Malik, N. A. (2024) · Advances in information security, privacy, and ethics book series · doi:10.4018/979-8-3693-5415-5.ch010 · Cited by 13 · see citing works
Mathieu, B., Neumann, A., Paviot, T., Robert, P., & Lamouri, S. (2024) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-024-02509-w · Cited by 14 · see citing works
“In the manufacturing sector, it can be used for tasks such as intelligent fault analysis (Wang et al., 2023), automating responses to customer queries (Olujimi & Ade-Ibijola, 2023), and extracting innovative information from patent texts (Berdyugina & Cavallucci, 2023).”
Yuan, Y., Zhou, H., Wang, B., Li, C., Gong, B., & Li, Z. (2026) · International Dental Journal · doi:10.1016/j.identj.2025.109336 · Cited by 12 · see citing works
“NLP facilitates EMR automation, including speech-to-text conversion and structured data generation.”
InfluentialPham, H. V., & Moore, P. T. (2024) · Information · doi:10.3390/info15070381 · Cited by 11 · see citing works
Bridging the Gap: ChatGPT’s Role in Enhancing STEM Education
Luan, L., Lin, X. Y., & Dai, Y. (2025) · Open Praxis · doi:10.55982/openpraxis.17.1.685 · Cited by 16 · see citing works
Social Conflicts in South Korean Public Construction Projects: Insights Using a Large Language Model
Namgoong, D., Baek, S., Won, J. W., & Han, S. H. (2025) · Journal of Management in Engineering · doi:10.1061/jmenea.meeng-6705 · Cited by 10 · see citing works
Madsen, D. Ø., & Toston, D. M. (2025) · Digital · doi:10.3390/digital5030024 · Cited by 14 · see citing works
“It has advanced through several iterations, from GPT-2 to GPT-4, each contributing improvements in accuracy, coherence, and safety [7–9].”
Chen, S., & Lin, Y. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1619489 · Cited by 10 · see citing works
Investigating the attitude of university students towards the use of ChatGPT as a learning resource
Estrada-Araoz, E. G., Valverde, Y. P., Quispe-Herrera, R., Ramos, N. A. G., Rivera-Mamani, F. A., & Claros, A. R. (2024) · Data & Metadata · doi:10.56294/dm2024268 · Cited by 13 · see citing works
Parker, L., Loper, A. J., Carter, C. W., Hayes, J., & Karakas, A. (2026) · Computers and Education Open · doi:10.1016/j.caeo.2025.100329 · Cited by 10 · see citing works
Wang, J. (2024) · Journal of Technical Writing and Communication · doi:10.1177/00472816241260033 · Cited by 10 · see citing works
“As Nazir and Wang (2023) posited, ChatGPT ’ s limitations warrant further research to improve the model ’ s performance and responsible use.”
Malhotra, K., Wiesenfeld, B. M., Major, V. J., Grover, H., Aphinyanaphongs, Y., Testa, P. A., & Austrian, J. S. (2024) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocae285 · Cited by 9 · see citing works
Exploring ChatGPT applications in healthcare: a comprehensive overview
Masood, S., Bashrawi, M. A. A., Khan, M. A., & Nazir, A. (2024) · The Visual Computer · doi:10.1007/s00371-024-03697-5 · Cited by 10 · see citing works
“It has been estimated by Smith et al. [86] that AI can lead to significant enhancement of the accuracy of surgical procedures, resulting in improved outcomes in those high-consequence environments where precision counts [92].”
Self-citationNowacki, L., & Wrochna, A. E. (2025) · E-Learning and Digital Media · doi:10.1177/20427530251331083 · Cited by 9 · see citing works
Cordero, J., & Cordero-Castillo, A. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-85930-4_23 · Cited by 13 · see citing works
Blind Faith? User Preference and Expert Assessment of AI-Generated Religious Content
Alam, S., Abdulhai, M., & Salehi, N. (2025) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3715275.3732162 · Cited by 9 · see citing works
Bridging AI chatbot use and critical thinking: the mediating role of AI literacy
Badali, M., Shahalizadeh, M., Alimirzaie, M., Noroozi, O., & Banihashem, S. K. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2025.2605487 · Cited by 9 · see citing works
“For example, ChatGPT can generate responses that appear credible, yet may contain factual inac-curacies, leading to the inadvertent spread of misinformation (Nazir & Wang, 2023).”
Casey, J. C., Dworkin, M. S., Winschel, J. M., Bacic, J. D., Daher, M., Katarincic, J. A., Gil, J. A., & Akelman, E. (2024) · Hand surgery & rehabilitation · doi:10.1016/j.hansur.2024.101757 · Cited by 9 · see citing works
Generative artificial intelligence in management research: a practical guide on mistakes to avoid
Lorenz, F., Lorenzen, S., Franco, M., Velz, J., & Clauß, T. (2024) · Management Review Quarterly · doi:10.1007/s11301-024-00469-2 · Cited by 8 · see citing works
“Generative AI’s limitations become evident in its lack of domain-specific knowledge, posing a challenge to generating specialized academic content that fully grasps the depth and complexity of subject-specific discourses (Nazir and Wang 2023).”
Wiangkham, A., & Vongvit, R. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.128188 · Cited by 12 · see citing works
Mabwe, K., Aminu, N., Ivanov, S. H., & Dimov, D. (2025) · foresight · doi:10.1108/fs-06-2024-0122 · Cited by 8 · see citing works
Ying, H., Zhao, Z., Zhao, Y., Zeng, S., & Yu, S. (2024) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocae115 · Cited by 7 · see citing works
Li, Y., Yan, Y., Tong, Z., Wang, Y., Yang, Y., Bai, M., Pu, D., Xie, J., Liu, C., Li, B., et al. (2025) · Applied Soft Computing · doi:10.1016/j.asoc.2025.113084 · Cited by 7 · see citing works
Oladokun, B. D., Enakrire, R. T., Emmanuel, A. K., Ajani, Y. A., & Adetayo, A. J. (2025) · Journal of Web Librarianship · doi:10.1080/19322909.2025.2482093 · Cited by 7 · see citing works
“5 architecture, which represents an evolution from earlier models by offering enhanced language understanding, coherence, and response quality (Nazir & Wang, 2023).”
Silva, R. R., de Lima, B. E., José, G., Cordeiro, D. F., Viana, R. B., Andrade, M. S., Vancini, R. L., Rosemann, T. J., Weiss, K., Knechtle, B., et al. (2024) · Epilepsy & Behavior Reports · doi:10.1016/j.ebr.2024.100692 · Cited by 7 · see citing works
“This functionality provides access to a broader range of knowledge and facilitates more intuitive interactions with advanced technology [21].”
BackgroundHisamatsu, T., Fukuda, M., Kinuta, M., & Kanda, H. (2024) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.65240 · Cited by 7 · see citing works
“Third, the version of ChatGPT used will be trained on data in the future, which may result in grasping the complexity and context of these issues 13) .”
Social Biases in AI-Generated Creative Texts: A Mixed-Methods Approach in the Spanish Context
Campos, M. A. G., Ayensa, J. I. B., & Padilla-Martínez, A. (2025) · Social Sciences · doi:10.3390/socsci14030170 · Cited by 9 · see citing works
Human-AI Collaboration: Understanding User Trust in ChatGPT Conversations
Hans, S., Kumar, B., Parihar, V., & singh, S. (2024) · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT · doi:10.55041/ijsrem27929 · Cited by 7 · see citing works
Correlates of Medical and Allied Health Students’ Engagement with Generative AI in Nigeria
Iliyasu, Z., Abdullahi, H. O., Iliyasu, B. Z., Bashir, H. A., Amole, T. G., Abdullahi, H. M., Abdullahi, A. U., Kwaku, A. A., Dahir, T., Tsiga-Ahmed, F. I., et al. (2024) · Medical Science Educator · doi:10.1007/s40670-024-02181-y · Cited by 10 · see citing works
“Among these advancements is ChatGPT, a prominent example of generative pre-trained transformers (GPTs), an AI-powered conversational chatbot introduced in 2022 [1].”
de Souza, A. F., Verri, F. A. N., Campos, P. H. D. S., & Balestrassi, P. P. (2025) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-025-15701-w · Cited by 6 · see citing works
Hidayatullah, H. I., Saifullah, M. T., Ghozali, M. T., & Aziz, A. (2025) · Neuroscience Informatics · doi:10.1016/j.neuri.2025.100213 · Cited by 6 · see citing works
Comparing AI-Generated Responses: A Study on ChatGPT, Gemini, and Copilot in Education
Boral, K., & Mondal, K. K. (2025) · Journal of Educational Technology Systems · doi:10.1177/00472395251368385 · Cited by 6 · see citing works
“ChatGPT incorporates multimodal functionality, enabling it to analyse and interpret both text and images to create and understand content (Nazir & Wang, 2023).”
How is language intelligence evolving? A multi-dimensional survey of large language models
Chen, X., Zhou, L., Chen, J., Wang, G., & Li, X. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.130637 · Cited by 7 · see citing works
Wang, X., Long, Z., Zhu, B., Cao, Y., Tang, H., He, K., & Zhang, S. (2026) · Scientific Reports · doi:10.1038/s41598-025-31874-6 · Cited by 6 · see citing works
Chang, B. R., Tsai, H. F., & Chen, C. H. (2026) · Electronics · doi:10.3390/electronics15020353 · Cited by 6 · see citing works
The Application of DeepSeek in English language Classrooms
Ali, M. M., Anwar, M. N., & Zahid, M. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-9077-1.ch001 · Cited by 6 · see citing works
Fen Öğretiminde ChatGPT Kullanımı Hakkında Öğrenci Görüşleri
Torun, B., & Karamustafaoğlu, O. (2025) · Cumhuriyet International Journal of Education · doi:10.30703/cije.1609145 · Cited by 5 · see citing works
Zhang, X., Wang, Y., He, A., Wang, H., & Li, T. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.129423 · Cited by 5 · see citing works
Leong, Y. H., Nambiar, L., Tay, V. Y. J., Lie, S. A., & Yuhe, K. (2025) · JMIR Formative Research · doi:10.2196/77580 · Cited by 5 · see citing works
“This supports the argument that domain-specialized enhancements improve both learner experience and perceived educational value [27].”
- Authors
- Nazir, A., & Wang, Z.
- Affiliations
- University of Maryland, Baltimore (US)
- Corresponding author
- Wang, Ze
- ORCID
- Venue
- Meta-Radiology
- Publisher
- Elsevier BV
- Published
- 2023-09
- Volume
- 1
- Issue
- 2
- Pages
- 100022
- ISSN
- 2950-1628 (ISSN-L)
- PMC
- PMC10611551
- OpenAlex
- W4387425757
- Semantic Scholar
- 3cc896b9a9c4951510b6b9f28be930d65b24d29f
- Cited by
- 245
- References
- 103
- Citations by year
- 2026: 47 · 2025: 99 · 2024: 95 · 2023: 4
- FWCI
- 23.10
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Meta-Radiology (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health (R01AG060054, 1UL1TR003098, R01AG070227, R01EB031080-01A1, P41EB029460-01A1)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Keywords
- ChatGPT, large language models, generative pre-trained transformer, chatbots, natural language generation, natural language understanding, ethical considerations, trustworthy AI
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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