Cited by 101Artificial Intelligence in Healthcare and EducationMachine Learning in HealthcareArtificial Intelligence in Education

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On the cusp: Considering the impact of artificial intelligence language models in healthcare

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Goodman, Rachel S., Patrinely, J. Randall, Osterman, Travis, Wheless, Lee, Johnson, Douglas B.·2023·Med

DOI 10.1016/j.medj.2023.02.008

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Abstract

Goodman et al. discuss how AI technologies like the natural language processing model Chat-GPT could potentially transform healthcare through knowledge dissemination and personalized patient education. Before these tools can be safely integrated into healthcare, research and development of robust oversight mechanisms are necessary to ensure their accuracy and reliability.

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“…has been recently described as having substantial power to advance academia and librarianship (Lund & Wang, 2023) and to transform healthcare (Goodman et al., 2023) in both ‘ anxiety-provoking and exciting new ways ’ (Lund & Wang, 2023, p. 1), thus reflecting a potentially profound change…”
Background
Assessing the quality of artificial intelligence–generated patient counseling for rhinosinusitis
Hill, G. S., Fischer, J. L., Watson, N. L., Riley, C. A., & Tolisano, A. M. (2024) · International Forum of Allergy & Rhinology · doi:10.1002/alr.23387 · Cited by 4
Physicians' Perspectives on ChatGPT in Ophthalmology: Insights on Artificial Intelligence (AI) Integration in Clinical Practice
Ahmed, A. E., Fatani, D. R., Vargas, J. M., AlMutlak, M., Helayel, H. B., Fairaq, R., & Alabdulhadi, H. (2025) · Cureus · doi:10.7759/cureus.78069 · Cited by 5
“Several studies reported the application of ChatGPT in generating medical articles, such as literature reviews, case studies, and research summaries [4].”
Different artificial neural networks for predicting burnout risk in Italian anesthesiologists
Cascella, M., Simonini, A., Coluccia, S., Bignami, E. G., Fiore, G., Petrucci, E., Vergallo, A., Sollecchia, G., Marinangeli, F., Pedone, R., et al. (2025) · Journal of Anesthesia Analgesia and Critical Care · doi:10.1186/s44158-025-00255-w · Cited by 3
Is ChatGPT a Reliable Source of Information about Dental Bleaching Treatment?
Tonga, G. (2025) · Selcuk Dental Journal · doi:10.15311/selcukdentj.1554003 · Cited by 3
Investigating patients’ perceptions of ChatGPT as a health information resource: A qualitative study
AlShammary, M. H., Alyahya, N. M., Alanazi, E. M., Aldaeej, A. A., Alanazi, A. M., Hassan, W., Farag, T. H., Alanazi, S. M., Otaibi, H. M. A., Albagmi, S., et al. (2025) · Nutrition and Health · doi:10.1177/02601060251376091 · Cited by 3
“Although studies (Biswas, 2023; Cascella et al., 2023; Goodman et al., 2023; Khan et al., 2023; Seth et al., 2023) found that ChatGPT applications were very relevant to the health-care industry, they also noted the need for more research to properly comprehend ChatGPT ’ s effects on patients ’…”
Advancing dermatology: embracing the power of artificial intelligence. Comment on ‘Artificial intelligence-assisted publishing in five prominent dermatology journals: a quantitative study of recent publications’
Potestio, L., Martora, F., Villani, A., Cacciapuoti, S., Battista, T., & Megna, M. (2023) · Clinical and Experimental Dermatology · doi:10.1093/ced/llad281 · Cited by 3
ChatGPT in Nuclear Medicine: Expanding Possibilities and Navigating Challenges
Khangembam, B. C. (2024) · Indian Journal of Nuclear Medicine · doi:10.4103/ijnm.ijnm_67_23 · Cited by 3
“[1] By delivering accurate and personalized information, ChatGPT can help patients better understand nuclear medicine procedures, thereby reducing anxiety and improving the overall patient experience.”
Background
Exploring the Chat GPT's Impact and Prospects for Business Research Purposes
Kurnianingrum, D., Jumbri, I. A., Ratnapuri, C. I., Karmagatri, M., & Kartawinata, B. R. (2024) · International Conference for Innovation in Technology (INOCON) · doi:10.1109/inocon60754.2024.10511483 · Cited by 3
Evaluation of the Quality of ChatGPT’s Responses to Top 20 Questions about Robotic Hip and Knee Arthroplasty: Findings, Perspectives and Critical Remarks on Healthcare Education
Venosa, M., Calvisi, V., Iademarco, G., Romanini, E., Ciminello, E., Cerciello, S., & Logroscino, G. (2024) · Prosthesis · doi:10.3390/prosthesis6040066 · Cited by 3
“914 Nevertheless, the adoption of robotic systems in orthopedic surgery comes with a set of challenges, including cost considerations, a learning curve for surgeons, and limitations in speci ﬁ c clinical scenarios.”
Background
Can Large Language Models Provide Emergency Medical Help Where There Is No Ambulance? A Comparative Study on Large Language Model Understanding of Emergency Medical Scenarios in Resource-Constrained SettingsPreprint
Mensah, P. B., Quao, N. S. A., & Dagadu, S. (2024) · medRxiv · doi:10.1101/2024.04.17.24305971 · Cited by 4
Assessing the Quality of AI-Generated Responses to Botulinum Toxin Applications in Bruxism Therapy
Zi̇nci̇r, Ö. Ö., Özkan, E. Ç., & Hati̇poğlu, Ş. (2025) · Journal of Craniofacial Surgery · doi:10.1097/scs.0000000000012195 · Cited by 2
Pilot Study on AI Image Analysis for Lower-Limb Reconstruction—Assessing ChatGPT-4’s Recommendations in Comparison to Board-Certified Plastic Surgeons and Resident Physicians
Graul, S., Pais, M. A., Loucas, R., Rohrbach, T., Volkmer, E., Leitsch, S., & Holzbach, T. (2025) · Life · doi:10.3390/life15010066 · Cited by 2
“Task-specific LLMs trained on curated medical datasets could offer more reliable support, ensuring relevance and minimizing risks associated with erroneous outputs [3,10]. plastic surgery.”
Influential
ChatGPT and American Society of Anesthesiologists (ASA) classifications - utilizing artificial intelligence in ASA classification of pediatric surgical patients
Challa, C. K., Ahmed, A. K., Geng‐Ramos, G., Luu, J., Rana, S., & Cronin, J. A. (2025) · Perioperative Care and Operating Room Management · doi:10.1016/j.pcorm.2025.100547 · Cited by 2
What artificial intelligence (AI) can tell us about Nasoalveolar Molding (NAM)?
Hati̇poğlu, Ş., Özkan, E. Ç., Taşova, F. A. K., & Zi̇nci̇r, Ö. Ö. (2025) · BMC Oral Health · doi:10.1186/s12903-025-06983-3 · Cited by 1
“Although online resources have become widely used to answer questions about health problems that individuals are trying to overcome, the accuracy and quality of the answers obtained from these resources are questionable [40].”
How Accurate Are the Responses of 4 AI Chatbots to Orthognathic Surgery Questions?
Hati̇poğlu, Ş., Özkan, E. Ç., Taşova, F. A. K., & Zi̇nci̇r, Ö. Ö. (2026) · Journal of Craniofacial Surgery · doi:10.1097/scs.0000000000012367 · Cited by 1
The OB-GYN Take on GPT: Objective Assessment of Artificial Intelligence Models in Patient Education
Burleson, L. K., Boardley, E., LaShell, A., & Shanks, A. L. (2026) · Cureus · doi:10.7759/cureus.101600 · Cited by 1
“LLMs are a subset of AI that generate responses based on patterns learned from large text datasets [2].”
Clinical Accuracy of AI Language Models in Providing Impacted Teeth Information: A Comparative Evaluation
Zi̇nci̇r, Ö. Ö., Özkan, E. Ç., & Hati̇poğlu, Ş. (2026) · Journal of Craniofacial Surgery · doi:10.1097/scs.0000000000012363 · Cited by 1
Is it time for the neurologist to use Large Language Models in everyday practice?Preprint
Maiorana, N. V., Marceglia, S. R. F., Treddenti, M., Tosi, M., Guidetti, M., Creta, M. F., Bocci, T., Oliveri, S., Boneschi, F. M., & Priori, A. (2025) · medRxiv · doi:10.1101/2025.01.23.25320945 · Cited by 1
“These generative language models, promise significant potential in assisting healthcare professionals, especially in diagnosis, medical treatments 6 and medical education 7 .”
Assessing the utility of artificial intelligence throughout the triage outpatientsPreprint
Liu, X., Lai, R., Yan, C., Jing, H., & Zhang, W. (2023) · Research Square · doi:10.21203/rs.3.rs-2957289/v1
Classification of Surgical Patients Needing Preoperative Cardiac Evaluations: A Comparison of General-Purpose and Domain-Specific Large Language Models (Preprint)Preprint
Tully, J. L., Litake, O., Meineke, M. N., Simpson, S., Waterman, R. S., & Gabriel, R. A. (2023) · doi:10.2196/preprints.52975
Unveiling the Reliability of ChatGPT Answers in the Biomedical Realm: An Assessment in the
Elbatanouny, H., Khater, T., Ansari, S., Khan, B., Khan, W., Almajali, E. R., Al‐Jumeily, D., & Hussain, A. J. (2023) · International Conference on Developments in eSystems Engineering (DeSE) · doi:10.1109/dese60595.2023.10469457 · Cited by 1
“Research and the creation of strong oversight systems are required before these tools can be securely integrated into healthcare to ensure their accuracy and dependability [19].”
BackgroundMethod
Accuracy and Completeness of Bard and Chat-GPT 4 Responses for Questions Derived from the International Consensus Statement on Endoscopic Skull-Base Surgery 2019
Abgin, Y., Umemoto, K. K., Goulian, A. J., Vasquez, M., Polster, S. P., Wu, A. W., Roxbury, C. R., Soni, P., Ahmed, O. G., & Tang, D. M. (2024) · Journal of Neurological Surgery Part B Skull Base · doi:10.1055/a-2436-4222
Evaluación cualitativa de modelos de inteligencia artificial generativa para resolución de preguntas clínicas de rehabilitación infantil
Palomer, D. G., & SPOERER, M. A. (2025) · Rehabilitación Integral · doi:10.51230/ri.v18i1.98 · Cited by 1
“Utilizando prompts adecuados, se podrían sintetizar revisiones con los deta-lles de los avances de varios campos o crear guías clínicas de patologías específicas en segundos 20,22 .”
ChatGPT: Boon or Bane
Mishra, S., & Lal, N. (2025) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-83549-852-120251002
ChatGPT in complex adaptive healthcare systems: embrace with caution
Olsson, A.-K., Arakelian, E., Lindberg, M., Göras, C., & Erikson, M. S. (2025) · International Journal of Electronic Healthcare · doi:10.1504/ijeh.2025.10071817
Constructing a Smart-Assistant for Improving the Outpatient Service Quality in Real-time: a Prospective Single-center Cohort StudyPreprint
Du, H., Li, J., Xiao, B., Wang, X., Xue, W., Deng, M., Tan, S., Wang, J., Luo, C., Chen, B., et al. (2025) · Research Square · doi:10.21203/rs.3.rs-7066667/v1
Evaluating the validity, safety, and usefulness of ChatGPT in providing information on adolescent idiopathic scoliosis: a study of digital health resources for patients and families
Tunc, H., Akdag, E. P. K., & Tarakci, D. (2025) · AI and Ethics · doi:10.1007/s43681-025-00845-y
Enhancing Readability of Consumer Health Information on Spinal Cord Injury through a Self-Reflection Rewriting Method (Preprint)Preprint
Aryoyudanta, B., Yuliana, M., Setiawan, I. M. A., Saptono, A., Dicianno, B. E., Choi, Y. K., & Parmanto, B. (2026) · doi:10.2196/preprints.93051
Leveraging ChatGPT to assist junior physicians in standardizing ultrasound report writing: A promising tool
Zhu, L., Zhong, H., Bai, J., Wang, X., Huang, P., & Xu, Z. (2026) · Digital Health · doi:10.1177/20552076261438675
ChatGPT in Orthopedic Trauma: Consistency, Accuracy, and Agreement With Textbook and Expert Opinion
Ronel, D., Shapiro, G., Ben-Kiki, T., & Keren, Y. (2026) · Cureus · doi:10.7759/cureus.110069
“It is important to remember that AI is not always consistent, and hallucinations are a critical safety issue [16,17].”
Up-to-Date Progress, Future Challenges and Future of Artificial Intelligence in Dermatology: From Diagnosis, Drug Discovery and Clinical Pathway
Li, Z., Chen, K., Ji, Y., Wu, H., & Lu, Q. (2026) · Skin · doi:10.2738/skin.2026.0011
Evaluating the accuracy of artificial intelligence-generated patient counseling for vestibular schwannoma
Sommerfeldt, J. M., Pierre, J. J., Fischer, J. L., RILEY, C. A., & Tolisano, A. M. (2026) · American Journal of Otolaryngology · doi:10.1016/j.amjoto.2026.104948

Authors: Goodman, R. S., Patrinely, J. R., Osterman, T., Wheless, L., & Johnson, D. B.
Affiliations: Vanderbilt University (US)
Vanderbilt University Medical Center (US)
Corresponding author: Johnson, Douglas B.
ORCID: Goodman, Rachel S.
Patrinely, J. Randall
Osterman, Travis
Wheless, Lee
Johnson, Douglas B.
Venue: Med
Publisher: Elsevier BV
Published: 2023-03
Volume: 4
Issue: 3
Pages: 139-140
ISSN: 2666-6340 (ISSN-L)
DOI: 10.1016/j.medj.2023.02.008
OpenAlex: W4323835279
Cited by: 100
References: 2
Citations by year: 2026: 9 · 2025: 31 · 2024: 33 · 2023: 27
FWCI: 3.99
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
www.elsevier.com/open-access/userlicense/1.0/ (vor, 375 d)
Locations: Med (publishedVersion)
PubMed (publishedVersion)
Funders: National Cancer Institute (R01CA227481)
Bristol-Myers Squibb
Incyte
Topics: Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
Social Sciences › Education › Artificial Intelligence in Education
Keywords: artificial intelligence in healthcare, large language models, ChatGPT, natural language processing, personalized patient education, knowledge dissemination, human oversight of AI
MeSH terms: Artificial Intelligence, Delivery of Health Care, Health Facilities, Humans, Natural Language Processing, Reproducibility of Results

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On the cusp: Considering the impact of artificial intelligence language models in healthcare

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