Quality of ChatGPT Responses to Questions Related To Liver Transplantation

Endo, Yutaka; Sasaki, Kazunari; Moazzam, Zorays; Lima, Henrique A.; Schenk, Austin D.; Limkemann, Ashley; Washburn, W. Kenneth; Pawlik, Timothy M.

doi:10.1007/s11605-023-05714-9

Cited by 18 publications

(9 citation statements)

References 5 publications

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“…Specifically, more than 70% of the responses received ratings of “very good” or “excellent”. Most of the interviewed experts believed that patients could utilize ChatGPT as an initial resource to address uncertainties 6 . Research in periodontal disease, breast reconstruction, otolaryngology, dermatology and other areas has also shown that ChatGPT is adept at addressing patients’ concerns 7 – 10 .…”

Section: Chatgpt In Medicine: Prospectsmentioning

confidence: 99%

ChatGPT in medicine: prospects and challenges: a review article

Tan,

Xin,

2024

International Journal of Surgery

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It has been a year since the launch of Chat Generator Pre-Trained Transformer (ChatGPT), a generative artificial intelligence (AI) program. The introduction of this cross-generational product initially brought a huge shock to people with its incredible potential, and then aroused increasing concerns among people. In the field of medicine, researchers have extensively explored the possible applications of ChatGPT and achieved numerous satisfactory results. However, opportunities and issues always come together. Problems have also been exposed during the applications of ChatGPT, requiring cautious handling, thorough consideration and further guidelines for safe use. Here, we summarized the potential applications of ChatGPT in the medical field, including revolutionizing healthcare consultation, assisting patient management and treatment, transforming medical education and facilitating clinical research. Meanwhile, we also enumerated researchers’ concerns arising along with its broad and satisfactory applications. As it is irreversible that AI will gradually permeate every aspect of modern life, we hope that this review can not only promote people’s understanding of the potential applications of ChatGPT in the future, but also remind them to be more cautious about this “Pandora’s Box” in the medical field. It is necessary to establish normative guidelines for its safe use in the medical field as soon as possible.

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Section: Chatgpt In Medicine: Prospectsmentioning

confidence: 99%

ChatGPT in medicine: prospects and challenges: a review article

Tan,

Xin,

2024

International Journal of Surgery

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“…DL has gained prominence within the broader field of AI due to its ability to process data in a hierarchical fashion, thereby allowing for more sophisticated and nuanced decision making [26] . DL techniques, particularly convolutional neural networks (CNN), have been applied to radiomics, which is a field of medical imaging that involves extracting a large number of quantitative features from medical images [27] . NLP encompasses the interaction between computers and human language, including tasks such as speech recognition, language translation, sentiment analysis, and language understanding.…”

Section: Application Of Ai In the Medical Fieldmentioning

confidence: 99%

Application of artificial intelligence to hepatobiliary cancer clinical outcomes research

Endo,

Alaimo,

Catalano

et al. 2024

Art Int Surg

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The rapid evolution of modern technology has made artificial intelligence (AI) an important emerging tool in healthcare. AI, which is a broad field of computer science, can be used to develop systems or machines equipped with the ability to tackle tasks that traditionally necessitate human intelligence. AI can be used to perform multifaceted tasks that involve the synthesis of large amounts of data with the generation of solutions, algorithms, and decision support tools. Various AI approaches, including machine learning (ML) and natural language processing (NLP), are increasingly being used to analyze vast healthcare datasets. In addition, visual AI has the potential to revolutionize surgery and the intraoperative experience for surgeons through augmented reality enhancing surgical navigation in real-time. Specific applications of AI in hepatobiliary tumors such as hepatocellular carcinoma and biliary tract cancer can improve patient diagnosis, prognostic risk stratification, as well as treatment allocation based on ML-based models. The integration of radiomics data and AI models can also improve clinical decision making. We herein review how AI may be of particular interest in the care of patients with complex cancers, such as hepatobiliary tumors, as these patients often require a multimodal treatment approach.

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“…The review of their full texts enabled the exclusion of 7 citations, and finally, 18 studies were included. [35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52] The excluded studies had unrelated tasks (n = 4, with tasks related to question generation or report summary) or unrelated settings (n = 3, addressing questions not strictly related to gastroenterology and hepatology; Table S3).…”

Section: Re Sultsmentioning

confidence: 99%

“…The main study characteristics are summarised in [44][45][46][47][48] and 1 (5.5%) focused on pancreatic disease. 41 All studies used ChatGPT from OpenAI, though some studies (n = 3, 13.7%) investigated multiple LLMs, including Bard from Google 36,44 and YouChat or BingChat.…”

Section: Study Characteristicsmentioning

confidence: 99%

“…For studies with available question lists, the average number of questions asked per study was 40.5 (±38.4), with a maximum of 164 48 and a minimum of 8 37 questions, with 9 (50%) studies failing to provide clear information on how the questions were generated. 35,36,39,41,43,44,46,47,50 In terms of question availability, 2 (14.3%) studies reported only partial lists, 38,39 and 3 (21.4%) studies reported only case summaries or keywords without a clear prompt to address the aims of the study. 42-44…”

Section: Question Generationmentioning

confidence: 99%

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Systematic review: The use of large language models as medical chatbots in digestive diseases

Giuffrè,

Kresevic,

You

et al. 2024

Aliment Pharmacol Ther

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SummaryBackgroundInterest in large language models (LLMs), such as OpenAI's ChatGPT, across multiple specialties has grown as a source of patient‐facing medical advice and provider‐facing clinical decision support. The accuracy of LLM responses for gastroenterology and hepatology‐related questions is unknown.AimsTo evaluate the accuracy and potential safety implications for LLMs for the diagnosis, management and treatment of questions related to gastroenterology and hepatology.MethodsWe conducted a systematic literature search including Cochrane Library, Google Scholar, Ovid Embase, Ovid MEDLINE, PubMed, Scopus and the Web of Science Core Collection to identify relevant articles published from inception until January 28, 2024, using a combination of keywords and controlled vocabulary for LLMs and gastroenterology or hepatology. Accuracy was defined as the percentage of entirely correct answers.ResultsAmong the 1671 reports screened, we identified 33 full‐text articles on using LLMs in gastroenterology and hepatology and included 18 in the final analysis. The accuracy of question‐responding varied across different model versions. For example, accuracy ranged from 6.4% to 45.5% with ChatGPT‐3.5 and was between 40% and 91.4% with ChatGPT‐4. In addition, the absence of standardised methodology and reporting metrics for studies involving LLMs places all the studies at a high risk of bias and does not allow for the generalisation of single‐study results.ConclusionsCurrent general‐purpose LLMs have unacceptably low accuracy on clinical gastroenterology and hepatology tasks, which may lead to adverse patient safety events through incorrect information or triage recommendations, which might overburden healthcare systems or delay necessary care.

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Quality of ChatGPT Responses to Questions Related To Liver Transplantation

Cited by 18 publications

References 5 publications

ChatGPT in medicine: prospects and challenges: a review article

ChatGPT in medicine: prospects and challenges: a review article

Application of artificial intelligence to hepatobiliary cancer clinical outcomes research

Systematic review: The use of large language models as medical chatbots in digestive diseases

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