Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.5
2.4
Journals
Healthcare
Special Issues
Leveraging ChatGPT and Large Language Models for Healthcare Advancements: Applications,...
share announcement

Leveraging ChatGPT and Large Language Models for Healthcare Advancements: Applications, Challenges, and Future Directions

A special issue of Healthcare (ISSN 2227-9032).

Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 3641

Special Issue Editors

Dr. Marco Cascella

E-Mail Website
Guest Editor
Unit of Anesthesiology, Intensive Care Medicine and Pain Medicine, Department of Medicine, Surgery and Dentistry, University of Salerno, Salerno, Italy
Interests: awareness anesthesia; anesthesia brain monitoring; memory and anesthesia; postoperative delirium; postoperative cognitive dysfunction; opioids research; pain assessment
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Elena G. Bignami

E-Mail Website
Guest Editor
Anesthesiology, Critical Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, Viale Gramsci 14, 43126 Parma, Italy
Interests: vascular surgery; anaesthesia
Prof. Dr. Ornella Piazza

E-Mail Website
Guest Editor
1. University Hospital “San Giovanni di Dio e Ruggi d’Aragona”, 84131 Salerno, Italy
2. Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, 84084 Fisciano, Italy
Interests: sepsis; trauma; heart and lung failure
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The emergence of large language models (LLMs), with their natural language understanding capabilities, hold immense potential for transforming healthcare practices, diagnosis, treatment, and patient engagement. Notably, in healthcare, LLMs can be implemented for a multitude of applications such as medical diagnosis through natural language interactions, personalized patient education, automated medical record analysis, drug discovery, and sentiment analysis of patient feedback. However, while LLMs offer groundbreaking possibilities, challenges such as ethical considerations, patient privacy, model biases, and ensuring clinical accuracy necessitate thorough exploration.

Given these premises, the proposed Special Issue aims to explore the transformative role and impact of LLMs, including ChatGPT, on healthcare and the challenges that accompany their integration, by inviting scholars and practitioners from the fields of natural language processing, healthcare, and artificial intelligence to share their findings and exchange their insightful ideas. We believe that with your contributions this Special Issue will serve as an authoritative and indispensable resource for researchers, professionals, and the healthcare community at large.

Dr. Marco Cascella
Prof. Dr. Elena G. Bignami
Prof. Dr. Ornella Piazza
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Healthcare is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ChatGPT
  • artificial intelligence
  • large language models
  • healthcare

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

10 pages, 385 KiB  
Article
Custom GPTs Enhancing Performance and Evidence Compared with GPT-3.5, GPT-4, and GPT-4o? A Study on the Emergency Medicine Specialist Examination
by Chiu-Liang Liu, Chien-Ta Ho and Tzu-Chi Wu
Healthcare 2024, 12(17), 1726; https://doi.org/10.3390/healthcare12171726 - 30 Aug 2024
Cited by 2 | Viewed by 1477
Abstract
Given the widespread application of ChatGPT, we aim to evaluate its proficiency in the emergency medicine specialty written examination. Additionally, we compare the performance of GPT-3.5, GPT-4, GPTs, and GPT-4o. The research seeks to ascertain whether custom GPTs possess the essential capabilities and [...] Read more.
Given the widespread application of ChatGPT, we aim to evaluate its proficiency in the emergency medicine specialty written examination. Additionally, we compare the performance of GPT-3.5, GPT-4, GPTs, and GPT-4o. The research seeks to ascertain whether custom GPTs possess the essential capabilities and access to knowledge bases necessary for providing accurate information, and to explore the effectiveness and potential of personalized knowledge bases in supporting the education of medical residents. We evaluated the performance of ChatGPT-3.5, GPT-4, custom GPTs, and GPT-4o on the Emergency Medicine Specialist Examination in Taiwan. Two hundred single-choice exam questions were provided to these AI models, and their responses were recorded. Correct rates were compared among the four models, and the McNemar test was applied to paired model data to determine if there were significant changes in performance. Out of 200 questions, GPT-3.5, GPT-4, custom GPTs, and GPT-4o correctly answered 77, 105, 119, and 138 questions, respectively. GPT-4o demonstrated the highest performance, significantly better than GPT-4, which, in turn, outperformed GPT-3.5, while custom GPTs exhibited superior performance compared to GPT-4 but inferior performance compared to GPT-4o, with all p < 0.05. In the emergency medicine specialty written exam, our findings highlight the value and potential of large language models (LLMs), and highlight their strengths and limitations, especially in question types and image-inclusion capabilities. Not only do GPT-4o and custom GPTs facilitate exam preparation, but they also elevate the evidence level in responses and source accuracy, demonstrating significant potential to transform educational frameworks and clinical practices in medicine. Full article
(This article belongs to the Special Issue Leveraging ChatGPT and Large Language Models for Healthcare Advancements: Applications, Challenges, and Future Directions)
►▼ Show Figures

Figure 1

13 pages, 791 KiB  
Article
ChatGPT as an Information Source for Patients with Migraines: A Qualitative Case Study
by Pascal Schütz, Sina Lob, Hiba Chahed, Lisa Dathe, Maren Löwer, Hannah Reiß, Alina Weigel, Joanna Albrecht, Pinar Tokgöz and Christoph Dockweiler
Healthcare 2024, 12(16), 1594; https://doi.org/10.3390/healthcare12161594 - 10 Aug 2024
Viewed by 1350
Abstract
Migraines are one of the most common and expensive neurological diseases worldwide. Non-pharmacological and digitally delivered treatment options have long been used in the treatment of migraines. For instance, migraine management tools, online migraine diagnosis or digitally networked patients have been used. Recently, [...] Read more.
Migraines are one of the most common and expensive neurological diseases worldwide. Non-pharmacological and digitally delivered treatment options have long been used in the treatment of migraines. For instance, migraine management tools, online migraine diagnosis or digitally networked patients have been used. Recently, applications of ChatGPT are used in fields of healthcare ranging from identifying potential research topics to assisting professionals in clinical diagnosis and helping patients in managing their health. Despite advances in migraine management, only a minority of patients are adequately informed and treated. It is important to provide these patients with information to help them manage the symptoms and their daily activities. The primary aim of this case study was to examine the appropriateness of ChatGPT to handle symptom descriptions responsibly, suggest supplementary assistance from credible sources, provide valuable perspectives on treatment options, and exhibit potential influences on daily life for patients with migraines. Using a deductive, qualitative study, ten interactions with ChatGPT on different migraine types were analyzed through semi-structured interviews. ChatGPT provided relevant information aligned with common scientific patient resources. Responses were generally intelligible and situationally appropriate, providing personalized insights despite occasional discrepancies in interaction. ChatGPT’s empathetic tone and linguistic clarity encouraged user engagement. However, source citations were found to be inconsistent and, in some cases, not comprehensible, which affected the overall comprehensibility of the information. ChatGPT might be promising for patients seeking information on migraine conditions. Its user-specific responses demonstrate potential benefits over static web-based sources. However, reproducibility and accuracy issues highlight the need for digital health literacy. The findings underscore the necessity for continuously evaluating AI systems and their broader societal implications in health communication. Full article
(This article belongs to the Special Issue Leveraging ChatGPT and Large Language Models for Healthcare Advancements: Applications, Challenges, and Future Directions)
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop