ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope

By Partha Pratim Ray. Internet Things Cyber Phys. Syst., 2023

2,136 citations recorded by the source corpus.

Subfields: Health Informatics, Radiology, Nuclear Medicine and Imaging, Safety Research

View Paper: https://www.semanticscholar.org/paper/4651e2cff4e4f20bf6039c4719dbbe8cbe05b278

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In Health Informatics

In Radiology, Nuclear Medicine and Imaging

In Safety Research

Citations in the corpus

Natural Language Processing with Commonsense Knowledge: A Survey (2021, methodology): “It surpasses traditional methods like bag-of-words, word2vec [37], RoBERTa [38], and Chat-GPT [39] in accuracy, and is distinguished by its full interpretability, trustworthiness, and explainability.”
GPT (Generative Pre-Trained Transformer)— A Comprehensive Review on Enabling Technologies, Potential Applications, Emerging Challenges, and Future Directions (2023, background): “GPTs can support the identification of potentially fraudulent actions by examining past transaction data, user behaviour patterns, and recognized fraudulent tendencies [140].”
The ethics of ChatGPT in medicine and healthcare: a systematic review on Large Language Models (LLMs) (2024, background): “19,20 The healthcare and medical field, being particularly sensitive and heavily regulated, is notably susceptible to ethical dilemmas.”
Exploring students’ perspectives on Generative AI-assisted academic writing (2024, neutral): “Despite its many benefits, there are still challenges and concerns associated with using GenAI for academic writing tasks, including data privacy, intellectual property, students’ over-reliance on automated tools, and plagiarism (Lund & Wang, 2023; Ray, 2023; Tlili et al., 2023).”
Time Travel in LLMs: Tracing Data Contamination in Large Language Models (2023, background): “…models such as the GPT-3/3.5 family (Brown et al. 2020) and GPT-4 (OpenAI 2023; Bubeck et al. 2023), and, needless to say, raises questions on the validity of evaluations and benchmarks conducted so far (Chang et al. 2023; Zhu et al. 2023; Bordt & von Luxburg 2023; Ray 2023; Penedo et al. 2023).”