Cited by 245Topic ModelingSpeech and dialogue systemsNatural Language Processing Techniques

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A comprehensive survey of ChatGPT: Advancements, applications, prospects, and challenges

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Nazir, Anam, Wang, Ze·2023·Meta-Radiology

DOI 10.1016/j.metrad.2023.100022PMC PMC10611551

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Abstract

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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Influential
Applied Hedge Algebra Approach with Multilingual Large Language Models to Extract Hidden Rules in Datasets for Improvement of Generative AI Applications
Pham, H. V., & Moore, P. T. (2024) · Information · doi:10.3390/info15070381 · Cited by 11
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 18
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
ChatGPT and Digital Transformation: A Narrative Review of Its Role in Health, Education, and the Economy
Madsen, D. Ø., & Toston, D. M. (2025) · Digital · doi:10.3390/digital5030024 · Cited by 16
“It has advanced through several iterations, from GPT-2 to GPT-4, each contributing improvements in accuracy, coherence, and safety [7–9].”
A multidimensional comparison of ChatGPT, Google Translate, and DeepL in Chinese tourism texts translation: fidelity, fluency, cultural sensitivity, and persuasiveness
Chen, S., & Lin, Y. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1619489 · Cited by 10
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
Longitudinal insights into AI in education: Usage, ethics, and policy development in higher education
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
Improving ChatGPT's Competency in Generating Effective Business Communication Messages: Integrating Rhetorical Genre Analysis into Prompting Techniques
Wang, J. (2024) · Journal of Technical Writing and Communication · doi:10.1177/00472816241260033 · Cited by 11
“As Nazir and Wang (2023) posited, ChatGPT ’ s limitations warrant further research to improve the model ’ s performance and responsible use.”
Health system-wide access to generative artificial intelligence: the New York University Langone Health experience
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
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
“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-citation
ChatGPT theses. Identifying distinctive markers in AI-generated versus human-created texts: A multimodal analysis in university education
Nowacki, L., & Wrochna, A. E. (2025) · E-Learning and Digital Media · doi:10.1177/20427530251331083 · Cited by 11
Exploring the Potential of Generative AI in Education: Opportunities, Challenges, and Best Practices for Classroom Integration
Cordero, J., & Cordero-Castillo, A. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-85930-4_23 · Cited by 15
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 15
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 10
“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).”
ChatGPT: A concise Google alternative for people seeking accurate and comprehensive carpal tunnel syndrome information
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
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
“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).”
Comparative analysis of multi-criteria decision making methods for prioritizing influential factors of ChatGPT adoption in higher education
Wiangkham, A., & Vongvit, R. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.128188 · Cited by 12
Generative artificial intelligence chatbots in investment decision-making: a phantom menace or a new hope?
Mabwe, K., Aminu, N., Ivanov, S. H., & Dimov, D. (2025) · foresight · doi:10.1108/fs-06-2024-0122 · Cited by 8
CoRTEx: contrastive learning for representing terms via explanations with applications on constructing biomedical knowledge graphs
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
Efficient fine-tuning of small-parameter large language models for biomedical bilingual multi-task applications
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
Hallucitation in Scientific Writing: Exploring Evidence from ChatGPT Versions 3.5 and 4o in Responses to Selected Questions in Librarianship
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
“5 architecture, which represents an evolution from earlier models by offering enhanced language understanding, coherence, and response quality (Nazir & Wang, 2023).”
The potential of large language model chatbots for application to epilepsy: Let’s talk about physical exercise
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 6
“This functionality provides access to a broader range of knowledge and facilitates more intuitive interactions with advanced technology [21].”
Background
ChatGPT Responses to Clinical Questions in the Japan Atherosclerosis Society Guidelines for Prevention of Atherosclerotic Cardiovascular Disease 2022
Hisamatsu, T., Fukuda, M., Kinuta, M., & Kanda, H. (2024) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.65240 · Cited by 7
“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
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
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
“Among these advancements is ChatGPT, a prominent example of generative pre-trained transformers (GPTs), an AI-powered conversational chatbot introduced in 2022 [1].”
Predicting surface roughness in dry machining of AISI H13 steel: a comparison of machine learning and GPT-based models with ceramic cutting tool
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
Exploring community pharmacist's psychological intentions to adopt generative artificial intelligence (GenAI) chatbots for patient information, education, and counseling
Hidayatullah, H. I., Saifullah, M. T., Ghozali, M. T., & Aziz, A. (2025) · Neuroscience Informatics · doi:10.1016/j.neuri.2025.100213 · Cited by 9
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 9
“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 10
Evaluation of DeepSeek-R1 and ChatGPT-4o on the Chinese national medical licensing examination: a multi-year comparative study
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 7
Multimodal Intelligent Perception at an Intersection: Pedestrian and Vehicle Flow Dynamics Using a Pipeline-Based Traffic Analysis System
Chang, B. R., Tsai, H. F., & Chen, C. H. (2026) · Electronics · doi:10.3390/electronics15020353 · Cited by 6
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
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
TAPE: A multi-agent framework for task-adaptive planning and execution in resource-constrained environments
Zhang, X., Wang, Y., He, A., Wang, H., & Li, T. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.129423 · Cited by 9
Feasibility of a Specialized Large Language Model for Postgraduate Medical Examination Preparation: Single-Center Proof-Of-Concept Study
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
“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: Nazir, Anam
Wang, Ze
Venue: Meta-Radiology
Publisher: Elsevier BV
Published: 2023-09
Volume: 1
Issue: 2
Pages: 100022
ISSN: 2950-1628 (ISSN-L)
DOI: 10.1016/j.metrad.2023.100022
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: cc-by
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
creativecommons.org/licenses/by/4.0/ (vor, 36 d)
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

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A comprehensive survey of ChatGPT: Advancements, applications, prospects, and challenges

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