Cited by 245Topic ModelingSpeech and dialogue systemsNatural Language Processing Techniques

The DOI matches its Crossref record; 104 of the 104 references it cites were found in a registry or an index.

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

Open access

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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1 retracted

Retracted: Chat With ChatGPT on Intelligent Vehicles: An IEEE TIV Perspective
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“Figure 2 illustrates a bird-view to generic evidence based medicine that uses multimodal learning [11].”
Background
Assessing ChatGPT's cybersecurity implications in Saudi Arabian healthcare and education sectors: A comparative study
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Multimodal Machine Learning for Evidence Base Medicine
Mohammed, S., & Fiaidhi, J. (2024) · International Conference on Future Telecommunications and Artificial Intelligence (IC-FTAI) · doi:10.1109/ic-ftai62324.2024.10950070 · Cited by 1
“Figure 2 illustrates a bird-view to generic evidence based medicine that uses multimodal learning [11].”
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“Among the potential solutions proposed in the literature, the utilization of Artificial Intelligence (AI), especially natural language processing models such as ChatGPT 3 , is prominently emerging across various application domains [6].”
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“The design process incorporates user feedback and iterative refinement, ensuring alignment with user expectations and practical usability [63].”
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Ai, M., Wang, K., Wang, H., Zheng, C., & Zhang, Y. (2025) · IEEE International Conference on Privacy Computing and Data Security (PCDS) · doi:10.1109/pcds65695.2025.00043 · Cited by 1
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Wang, S. I. C., & Liu, E. Z. F. (2025) · IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt64023.2025.00081 · Cited by 1
“A. ChatGPT: Advancing Conversational AI First introduced by Open Artificial Intelligence in November 2022, ChatGPT is an advanced conversational AI model rooted in the Generative Pre-trained Transformer architecture [3].”
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“…with these frameworks often drawing upon metaphorical analogies that liken LLMs to various systems: technical assemblages of algorithms and data (Nazir & Wang, 2023 ), vast repositories of information (Singhal et al., 2023 ), or even rudimentary forms of human-like intelligence (Wake et al.,…”
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“Recent advances in large language models (LLMs) [1, 18, 22] such as ChatGPT and Gemini overcome these issues by modeling complex semantics and sustaining multi-turn dialogue, offering valuable insights for academic advisory systems.”
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Karnalim, O., Santiadi, S., Natalia, D., Wijaya, J. S., Rupilu, G. E., Ivanayus, Sarean, A. R., & Hassabian, G. A. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-07316-7_17 · Cited by 1
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Sawah, V. E., Bhardwaj, A., Pryke-Hobbes, A., Gamaleldin, D., Nice, J., Ang, C. S., & Martin, A. K. (2026) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2026.100383 · Cited by 2
Evaluating ChatGPT’s Ability to Answer Common Parent Questions on Avascular Necrosis in Children
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“4,5 Recently, the use of large language models has rapidly increased.”
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LLM-Driven Trajectory Prediction at Intersections with Chain-of-Thought Reasoning
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“The rapid advancements in large language models (LLMs), such as GPT-4 [3] and Llama-2 [4], have offered a novel perspective for understanding complex traffic scenarios and ignited interest in their application to motion forecasting tasks [5].”
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ChatGPT is a concise, comprehensive, and accurate alternative to Google for answering common hand therapy questions
Casey, J. C., Wang, L., Milner, J., Cusano, J., Daher, M., Carney, K., Gregorzek, S., Platz, M., & Gil, J. A. (2026) · Hand Therapy · doi:10.1177/17589983261444990 · Cited by 1
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Exploring the pathway from brand passion to evangelism: the moderating effects of AI-driven personalization with consumer engagement as a mediator
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What do I not know? How does AI affect critical thinking?
Weaver, B., Gillon, F., Belton, I., & Heron, G. (2026) · Criminology & Criminal Justice · doi:10.1177/17488958261453600 · Cited by 1
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Karthikeyan, V., Kirubakaran, G., Prakash, R. V., & Visu, Y. P. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-6824-4.ch002 · Cited by 2
ChatGPT und halluzinierte Referenzen in Artikeln aus ausgewählten Bereichen der Betriebswirtschaftslehre
Schlögl, C. (2024) · Information - Wissenschaft & Praxis · doi:10.1515/iwp-2024-2016 · Cited by 1
An interactive multi-task ESG classification method for Chinese financial texts
Zhang, H., Zhang, Y., Wang, X., Zhang, L., & Ji, L. (2024) · Applied Intelligence · doi:10.1007/s10489-024-06068-8 · Cited by 1
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Khetan, S. P., & Suvarna, S. S. (2024) · Global Cardiology Science and Practice · doi:10.21542/gcsp.2024.56 · Cited by 1
“Ethical, privacy, and contextual challenges must also be considered when integrating ChatGPT into chronic condition care 8 .”
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Lynch, C. J., Jensen, E., Gore, R. J., Zamponi, V., O’Brien, K., Feldhaus, B., Smith, K., Martinez, J. P., Munro, M. H., Ozkose, T. E., et al. (2025) · IEEE Access · doi:10.1109/access.2025.3600146 · Cited by 2
“Despite advances in fluency and style, challenges persist regarding the accountability, safety, reliability, and ethical use of LLMs for narrative generation [4], [5], [6], [7], [8], [9], [10].”
What should an Editor do in the beginning of artificial intelligence era?
Fodor, D. (2023) · Medical Ultrasonography · doi:10.11152/mu-4317 · Cited by 1
Chatty GPT: Radiology's New BFF or Just Another Trendy Tool?
Buckwalter, K. A. (2024) · Academic Radiology · doi:10.1016/j.acra.2024.02.048 · Cited by 1
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Bychkov, A., Laohawetwanit, T., & Pinto, D. G. (2024) · medRxiv · doi:10.1101/2024.04.05.24305405
Machine learning's impact on medical education and research: beneficial or detrimental?
Subramaniam, S. K., Gounder, P. K., Mahmood, A. A. R., Anandaram, H., Polevoy, G. G., & Pichandy, M. P. (2024) · International Journal of Public Health Science (IJPHS) · doi:10.11591/ijphs.v13i3.24330
ChatGPT in Cyber Onslaught and Fortification: Past, Present, and Future
Gunda, M., Manda, V., Naradasu, P., Mekala, S., & Bhattacharya, S. (2024) · IEEE International Conference for Convergence in Technology (I2CT) · doi:10.1109/i2ct61223.2024.10543384
The Use of ChatGPT in Acquiring Technical Term for Report Writing among Aircraft Maintenance Students
Thambirajah, J. I. (2024) · International Journal For Multidisciplinary Research · doi:10.36948/ijfmr.2024.v06i03.23153

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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