/pdf/chatgpt-utility-in-healthcare-education-research-and-90zynnvb.pdf

ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns

HomeRadiologyVol. 307, No. 2 PreviousNext Reviews and CommentaryEditorialChatGPT Is Shaping the Future of Medical Writing But Still Requires Human JudgmentFelipe C. Kitamura Felipe C. Kitamura Author AffiliationsFrom the Department of Applied Innovation and AI, Diagnósticos da América SA (Dasa), Av Das Nações Unidas, 7815 Pinheiros, São Paulo, SP, Brazil 05425-070; and Department of Neuroradiology, Universidade Federal de São Paulo, São Paulo, Brazil.Address correspondence to the author (email: [email protected]).Felipe C. Kitamura Published Online:Feb 2 2023https://doi.org/10.1148/radiol.230171See editorial bySom BiswasMoreSectionsFull textPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In References1. Lippmann W. A Preface to Politics. New York, NY: Mitchell Kennerley, 1913. Google Scholar2. Biswas S. ChatGPT and the Future of Medical Writing. Radiology 2023;307(2):e223312. Link, Google Scholar3. Vaswani A, Shazeer N, Parmar N, et al. Attention Is All You Need. arXiv preprint arXiv:1706.03762. https://arxiv.org/abs/1706.03762. Posted June 12, 2017. Accessed January 23, 2023. Google Scholar4. Brown TB, Mann B, Ryder N, et al. Language Models are Few-Shot Learners. arXiv preprint arXiv:2005.14165. https://arxiv.org/abs/2005.14165. Posted May 28, 2020. Accessed January 23, 2023. Google Scholar5. OpenAI. ChatGPT: Optimizing Language Models for Dialogue. https://openai.com/blog/chatgpt/. Published November 30, 2022. Accessed January 23, 2023. Google Scholar6. Shen Y, Heacock L, Elias J, et al. ChatGPT and Other Large Language Models Are Double-edged Swords. Radiology 2023;307(2):e230163. Link, Google Scholar7. Korngiebel DM, Mooney SD. Considering the possibilities and pitfalls of Generative Pre-trained Transformer 3 (GPT-3) in healthcare delivery. NPJ Digit Med 2021;4(1):93. Crossref, Medline, Google Scholar8. ChatGPT Generative Pre-trained TransformerZhavoronkov A. 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Google ScholarArticle HistoryReceived: Jan 24 2023Revision requested: Jan 25 2023Revision received: Jan 26 2023Accepted: Jan 26 2023Published online: Feb 02 2023 FiguresReferencesRelatedDetailsCited ByAppropriateness of Breast Cancer Prevention and Screening Recommendations Provided by ChatGPTHana L Haver, Emily B Ambinder, Manisha Bahl, Eniola T Oluyemi, Jean Jeudy, Paul H Yi, 4 April 2023 | Radiology, Vol. 0, No. 0ChatGPT and Other Large Language Models Are Double-edged SwordsYiqiu Shen, Laura Heacock, Jonathan Elias, Keith D. Hentel, Beatriu Reig, George Shih, Linda Moy, 26 January 2023 | Radiology, Vol. 307, No. 2The potential impact of ChatGPT in clinical and translational medicineVivian WeiwenXue, PingguiLei, William C.Cho2023 | Clinical and Translational Medicine, Vol. 13, No. 3ChatGPT—a foe or an ally?Om PrakashYadava2023 | Indian Journal of Thoracic and Cardiovascular SurgeryChatGPT and Publication EthicsFaridRahimi, AminTalebi Bezmin Abadi2023 | Archives of Medical ResearchIs ChatGPT a valid author?Jaime A.Teixeira da Silva2023 | Nurse Education in Practice, Vol. 68Artificial intelligence and ChatGPT between worst enemy and best friend: The two faces of a revolution and its impact on science and medical schoolsM.Aubignat, E.Diab2023 | Revue NeurologiqueChatGPT-coauthored conversation between a pediatrician and a taxi driverMohamad-HaniTemsah, AymanAl-Eyadhy, AmrJamal2023 | Pediatric ResearchThe future of medical education and research: Is ChatGPT a blessing or blight in disguise?Taha BinArif, UzairMunaf, IbtehajUl-Haque2023 | Medical Education Online, Vol. 28, No. 1Implications of large language models such as ChatGPT for dental medicineFlorinEggmann, RolandWeiger, Nicola U.Zitzmann, Markus B.Blatz2023 | Journal of Esthetic and Restorative DentistryChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid ConcernsMalikSallam2023 | Healthcare, Vol. 11, No. 6Accompanying This ArticleChatGPT and Other Large Language Models Are Double-edged SwordsJan 26 2023RadiologyChatGPT and the Future of Medical WritingFeb 2 2023RadiologyChatGPT- Special Radiology:AI Podcast CollaborationFeb 21 2023Default Digital Object SeriesEpisode 17: ChatGPT- Special Radiology Podcast CollaborationFeb 21 2023Default Digital Object SeriesRecommended Articles Adapting Scientific Conferences to the Realities Imposed by COVID-19Radiology: Imaging Cancer2020Volume: 2Issue: 4Lessons on LeadershipRadioGraphics2018Volume: 38Issue: 6pp. 1688-1693Deep Learning: An Update for RadiologistsRadioGraphics2021Volume: 41Issue: 5pp. 1427-1445Deep Learning: A Primer for RadiologistsRadioGraphics2017Volume: 37Issue: 7pp. 2113-2131Web-Based Video ConferencesRadioGraphics2020Volume: 40Issue: 5pp. 1309-1317See More RSNA Education Exhibits Neural Networks in Deep Learning: A Simplified Explanation for RadiologistsDigital Posters2019Leading a Multigenerational WorkforceDigital Posters2020Team Approach to Improving Radiologist Wellness: Process and ExamplesDigital Posters2020 RSNA Case Collection Duplicated Gallbladder RSNA Case Collection2021Acute COVID-19 virus infection RSNA Case Collection2020Lipoid proteinosisRSNA Case Collection2020 Vol. 307, No. 2 PodcastPodcastMetrics Altmetric Score PDF download 

ChatGPT Is Shaping the Future of Medical Writing but Still Requires Human Judgment.

ChatGPT

BACKGROUND ChatGPT, a popular new large language model (LLM) built by OpenAI, has shown impressive performance in a number of specialized applications. Despite the rising popularity and performance of AI, studies evaluating the use of LLMs for clinical decision support are lacking. PURPOSE To evaluate ChatGPT's capacity for clinical decision support in radiology via the identification of appropriate imaging services for two important clinical presentations: breast cancer screening and breast pain. MATERIALS AND METHODS We compared ChatGPT's responses to the American College of Radiology (ACR) Appropriateness Criteria for breast pain and breast cancer screening. Our prompt formats included an open-ended (OE) format, where ChatGPT was asked to provide the single most appropriate imaging procedure, and a select all that apply (SATA) format, where ChatGPT was given a list of imaging modalities to assess. Scoring criteria evaluated whether proposed imaging modalities were in accordance with ACR guidelines. RESULTS ChatGPT achieved an average OE score of 1.83 (out of 2) and a SATA average percentage correct of 88.9% for breast cancer screening prompts, and an average OE score of 1.125 (out of 2) and a SATA average percentage correct of 58.3% for breast pain prompts. CONCLUSION Our results demonstrate the feasibility of using ChatGPT for radiologic decision making, with the potential to improve clinical workflow and responsible use of radiology services.

/pdf/evaluating-chatgpt-as-an-adjunct-for-radiologic-decision-8g3cinm1.pdf

Evaluating ChatGPT as an Adjunct for Radiologic Decision-Making

In recent years, artificial intelligence (AI) and machine learning have been transforming the landscape of scientific research. Out of which, the chatbot technology has experienced tremendous advancements in recent years, especially with ChatGPT emerging as a notable AI language model. This comprehensive review delves into the background, applications, key challenges, and future directions of ChatGPT. We begin by exploring its origins, development, and underlying technology, before examining its wide-ranging applications across industries such as customer service, healthcare, and education. We also highlight the critical challenges that ChatGPT faces, including ethical concerns, data biases, and safety issues, while discussing potential mitigation strategies. Finally, we envision the future of ChatGPT by exploring areas of further research and development, focusing on its integration with other technologies, improved human-AI interaction, and addressing the digital divide. This review offers valuable insights for researchers, developers, and stakeholders interested in the ever-evolving landscape of AI-driven conversational agents. This study explores the various ways ChatGPT has been revolutionizing scientific research, spanning from data processing and hypothesis generation to collaboration and public outreach. Furthermore, the paper examines the potential challenges and ethical concerns surrounding the use of ChatGPT in research, while highlighting the importance of striking a balance between AI-assisted innovation and human expertise. The paper presents several ethical issues in existing computing domain and how ChatGPT can invoke challenges to such notion. This work also includes some biases and limitations of ChatGPT. It is worth to note that despite of several controversies and ethical concerns, ChatGPT has attracted remarkable attentions from academia, research, and industries in a very short span of time. 

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

HomeRadiologyVol. 307, No. 2 PreviousNext Reviews and CommentaryEditorialChatGPT and Other Large Language Models Are Double-edged SwordsYiqiu Shen , Laura Heacock, Jonathan Elias, Keith D. Hentel, Beatriu Reig, George Shih, Linda MoyYiqiu Shen , Laura Heacock, Jonathan Elias, Keith D. Hentel, Beatriu Reig, George Shih, Linda MoyAuthor AffiliationsFrom the Center for Data Science, New York University, 60 5th Ave, New York, NY 10011 (Y.S.); Department of Radiology, New York University School of Medicine, New York, NY (L.H., B.R., L.M.); and Departments of Primary Care (J.E.) and Radiology (K.D.H., G.S.), Weill Cornell Medicine, New York, NY.Address correspondence to Y.S. (email: [email protected]).Yiqiu Shen Laura HeacockJonathan EliasKeith D. HentelBeatriu ReigGeorge ShihLinda MoyPublished Online:Jan 26 2023https://doi.org/10.1148/radiol.230163See editorial bySom BiswasSee editorial byFelipe C. 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Link, Google ScholarArticle HistoryReceived: Jan 23 2023Revision requested: Jan 23 2023Revision received: Jan 23 2023Accepted: Jan 23 2023Published online: Jan 26 2023 FiguresReferencesRelatedDetailsCited ByChatGPT Is Shaping the Future of Medical Writing But Still Requires Human JudgmentFelipe C. Kitamura, 2 February 2023 | Radiology, Vol. 307, No. 2The Role and Limitations of Large Language Models Such as ChatGPT in Clinical Settings and Medical JournalismFurkan Ufuk, 7 March 2023 | Radiology, Vol. 0, No. 0The potential impact of ChatGPT in clinical and translational medicineVivian WeiwenXue, PingguiLei, William C.Cho2023 | Clinical and Translational Medicine, Vol. 13, No. 3Large language models (LLM) and ChatGPT: what will the impact on nuclear medicine be?Ian L.Alberts, LorenzoMercolli, ThomasPyka, GeorgePrenosil, KuangyuShi, AxelRominger, AliAfshar-Oromieh2023 | European Journal of Nuclear Medicine and Molecular ImagingTransformers, codes and labels: large language modelling for natural language processing in clinical radiologyDenisRemedios, AlexRemedios2023 | European RadiologyChatGPT—a foe or an ally?Om PrakashYadava2023 | Indian Journal of Thoracic and Cardiovascular SurgeryChatGPTDiveshSardana, Timothy R.Fagan, John TimothyWright2023 | The Journal of the American Dental AssociationThe promise and peril of ChatGPT in geriatric nursing education: What We know and do not knowXiangQi, ZhengZhu, BeiWu2023 | Aging and Health Research, Vol. 3, No. 2Authors in the Age of Language-generation AI: To be or not to be, is that Really the Question?José DaríoMartínez-Ezquerro2023 | Archives of Medical ResearchBeyond chatting: The opportunities and challenges of ChatGPT in medicine and radiologyJuan M. LavistaFerres, William B.Weeks, Linda C.Chu, Steven P.Rowe, Elliot K.Fishman2023 | Diagnostic and Interventional ImagingAttention is not all you need: the complicated case of ethically using large language models in healthcare and medicineStefanHarrer2023 | eBioMedicine, Vol. 90Chatting or cheating? The impacts of ChatGPT and other artificial intelligence language models on nurse educationEdmond Pui HangChoi, Jung JaeLee, Mu-HsingHo, Jojo Yan YanKwok, Kris Yuet WanLok2023 | Nurse Education Today, Vol. 125Is ChatGPT a valid author?Jaime A.Teixeira da Silva2023 | Nurse Education in Practice, Vol. 68Do Large Language Models Understand Chemistry? A Conversation with ChatGPTCayque MonteiroCastro Nascimento, André SilvaPimentel2023 | Journal of Chemical Information and Modeling, Vol. 63, No. 6Readership Awareness Series – Paper 4: Chatbots and ChatGPT - Ethical Considerations in Scientific PublicationsMohammad JavedAli, AliDjalilian2023 | Seminars in OphthalmologyA SWOT analysis of ChatGPT: Implications for educational practice and researchMohammadrezaFarrokhnia, Seyyed KazemBanihashem, OmidNoroozi, ArjenWals2023 | Innovations in Education and Teaching InternationalChatGPT and other artificial intelligence applications speed up scientific writingTzeng-JiChen2023 | Journal of the Chinese Medical Association, Vol. 86, No. 4ChatGPT for tourism: applications, benefits and risksInêsCarvalho, StanislavIvanov2023 | Tourism ReviewImplications of large language models such as ChatGPT for dental medicineFlorinEggmann, RolandWeiger, Nicola U.Zitzmann, Markus B.Blatz2023 | Journal of Esthetic and Restorative DentistryAI and GPT for Management Scholars and Practitioners: Guidelines and ImplicationsSudhirRana2023 | FIIB Business Review, Vol. 12, No. 1Can ChatGPT improve communication in hospitals?DavidSantandreu-Calonge, PabloMedina-Aguerrebere, PatrikHultberg, Mariam-AmanShah2023 | El Profesional de la informaciónChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid ConcernsMalikSallam2023 | Healthcare, Vol. 11, No. 6Future Speech Interfaces with Sensors and Machine IntelligenceBruceDenby, Tamás GáborCsapó, MichaelWand2023 | Sensors, Vol. 23, No. 4Editorial: The Use of Artificial Intelligence (AI)-Assisted Technologies in Scientific DiscourseArvieVitente, RolandoLazaro, Catherine JoyEscuadra, JocelRegino, EsmeritaRotor2023 | Philippine Journal of Physical TherapyChatGPT and Big Data: Enhancing Text-to-Speech ConversionHatim AbdelhakDida, DSKChakravarthy, FazleRabbi2023 | Mesopotamian Journal of Big DataAn era of ChatGPT as a significant futuristic support tool: A study on features, abilities, and challengesAbidHaleem, MohdJavaid, Ravi PratapSingh2022 | BenchCouncil Transactions on Benchmarks, Standards and Evaluations, Vol. 2, No. 4Artificial intelligence and dental researchSMBalaji2022 | Indian Journal of Dental Research, Vol. 33, No. 4Accompanying This ArticleChatGPT and the Future of Medical WritingFeb 2 2023RadiologyChatGPT Is Shaping the Future of Medical Writing But Still Requires Human JudgmentFeb 2 2023RadiologyChatGPT- Special Radiology:AI Podcast CollaborationFeb 21 2023Default Digital Object SeriesEpisode 17: ChatGPT- Special Radiology Podcast CollaborationFeb 21 2023Default Digital Object SeriesRecommended Articles Deep Generative Adversarial Networks: Applications in Musculoskeletal ImagingRadiology: Artificial Intelligence2021Volume: 3Issue: 3Deep Learning: A Primer for RadiologistsRadioGraphics2017Volume: 37Issue: 7pp. 2113-2131Current Applications and Future Impact of Machine Learning in RadiologyRadiology2018Volume: 288Issue: 2pp. 318-328Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural NetworksRadiology2017Volume: 284Issue: 2pp. 574-582Convolutional Neural Networks for Radiologic Images: A Radiologist’s GuideRadiology2019Volume: 290Issue: 3pp. 590-606See More RSNA Education Exhibits Artificial Intelligence in Diagnostic Imaging: Current Applications and Future PerspectiveDigital Posters2019Artificial Intelligence in Breast Imaging: Past, Present, and FutureDigital Posters2020Generative Adversarial Networks (GANs): A Primer for RadiologistsDigital Posters2019 RSNA Case Collection Dynamic MRI findings of COVID-19 pneumoniaRSNA Case Collection2020Slow-growing cancerRSNA Case Collection2020Creutzfeldt-Jakob DiseaseRSNA Case Collection2021 Vol. 307, No. 2 PodcastPodcastMetrics Altmetric Score PDF download 

Jonathan Elias

Papers

ChatGPT and Other Large Language Models Are Double-edged Swords.