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Application of Artificial Intelligence in the Health Field or Education
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Application of Artificial Intelligence in the Health Field or Education

A special issue of European Journal of Investigation in Health, Psychology and Education (ISSN 2254-9625).

Deadline for manuscript submissions: 30 April 2025 | Viewed by 53554

Special Issue Editor

Dr. Hyunsu Lee

E-Mail Website
Guest Editor
Department of Physiology, School of Medicine, Pusan National University, Yangsan, Republic of Korea
Interests: Artificial Intelligence and neuroscience; neuroscience; machine learning; health informatics; medical education
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Artificial intelligence (AI) has been making waves across various sectors, and the fields of health and education are no exception. The application of AI in these domains has opened up a plethora of opportunities, paving the way for innovative solutions and transformative practices. In this context, this Special Issue aims to delve into the latest research, trends, and applications of AI in health and education.

This Special Issue will serve as a global platform for exploring the diverse aspects that influence the application of AI in health and education. We aim to discuss innovations in health diagnostics and treatment, personalized learning experiences, new educational management systems, and the evolving landscape of health and education in the era of AI.

We invite original research contributions from authors worldwide. We welcome research papers, case studies, and demonstrations that present original scientific results. Specifically, we are interested in empirical studies in health and education regarding the use of AI technologies, case studies about AI applications in these fields, new health and educational management systems leveraging AI, new evaluation techniques and tools, and best practices in AI for health and education.

We look forward to your valuable contributions to this Special Issue and to the ongoing discourse on the transformative potential of AI in health and education.

Best Regards,

Dr. Hyunsu Lee
Guest Editor

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. European Journal of Investigation in Health, Psychology and Education is an international peer-reviewed open access monthly 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 1400 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

  • artificial intelligence
  • AI practices for healthcare and education
  • innovation in health diagnostics and treatment
  • personalized learning experiences
  • new health and educational management systems leveraged by AI
  • novel evaluation techniques and tools

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Published Papers (10 papers)

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Research

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19 pages, 1099 KiB  
Article
Exploring Teacher Awareness of Artificial Intelligence in Education: A Case Study from Northern Cyprus
by Ahmet Güneyli, Nazım Serkan Burgul, Sonay Dericioğlu, Nazan Cenkova, Sinem Becan, Şeyma Elif Şimşek and Hüseyin Güneralp
Eur. J. Investig. Health Psychol. Educ. 2024, 14(8), 2358-2376; https://doi.org/10.3390/ejihpe14080156 - 12 Aug 2024
Viewed by 2368
Abstract
This study investigates the level of awareness among teachers regarding the use of artificial intelligence (AI) in education, focusing on whether this awareness varies according to socio-demographic characteristics, access to technology, and specific knowledge and beliefs about AI. Conducted in Northern Cyprus during [...] Read more.
This study investigates the level of awareness among teachers regarding the use of artificial intelligence (AI) in education, focusing on whether this awareness varies according to socio-demographic characteristics, access to technology, and specific knowledge and beliefs about AI. Conducted in Northern Cyprus during the 2023–2024 academic year, this study employed a survey model with purposive and snowball sampling methods, involving 164 teachers. Teachers at different levels, namely, primary school, secondary school, high school, and university, were included in this study. The “Artificial Intelligence Awareness Scale”, developed by Ferikoğlu and Akgün (2022), was used to measure AI awareness. Data normality was verified through skewness and kurtosis values, allowing for parametric statistical tests such as t-tests, one-way ANOVA, logistic regression, and chi-square analysis. This study explored the distribution of AI use across different school types and educational levels and assessed the impact of sub-dimensions of AI awareness on its application in teaching. Findings revealed no significant influence of teacher demographics (age, gender, education level, type of school, institution level, and monthly income) on AI awareness. However, usage patterns indicated that university lecturers were more likely to incorporate AI in their teaching, followed by primary and high school teachers, with secondary school teachers using it the least. A Multilayer Neural Network Analysis identified practical knowledge as the most critical factor influencing the use of AI in teaching (importance weight of 0.450), followed by beliefs and attitudes (0.298), relatability (0.148), and theoretical knowledge (0.104). These results highlight the importance of practical knowledge for fostering AI integration in educational practices, underscoring significant implications for teacher training and professional development programs. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in the Health Field or Education)
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15 pages, 1430 KiB  
Article
The Moderating Effects of Gender and Study Discipline in the Relationship between University Students’ Acceptance and Use of ChatGPT
by Ibrahim A. Elshaer, Ahmed M. Hasanein and Abu Elnasr E. Sobaih
Eur. J. Investig. Health Psychol. Educ. 2024, 14(7), 1981-1995; https://doi.org/10.3390/ejihpe14070132 - 8 Jul 2024
Cited by 2 | Viewed by 1956
Abstract
The intensive adoption of ChatGPT by university students for learning has encouraged many scholars to test the variables that impact on their use of such AI in their learning. This study adds to the growing body of studies, especially in relation to the [...] Read more.
The intensive adoption of ChatGPT by university students for learning has encouraged many scholars to test the variables that impact on their use of such AI in their learning. This study adds to the growing body of studies, especially in relation to the moderating role of students’ gender and their study discipline in their acceptance and usage of ChatGPT in their learning process. This study expanded the Unified Theory of Acceptance and Use of Technology (UTAUT) by integrating gender as well as study disciplines as moderators. The study collected responses from students in Saudi universities with different study disciplines and of different genders. The results of a structural model using Smart PLS showed a significant moderating effect of gender on the relationship between performance expectancy and ChatGPT usage. The results confirmed that the impact of performance expectancy in fostering ChatGPT usage was stronger in male than in female students. Moreover, social influence was shown to significantly affect males more than females in relation to ChatGPT usage. In addition, the findings showed that study discipline significantly moderates the link between social influence and ChatGPT usage. In the same vein, social influence significantly influences ChatGPT use in social sciences more than in applied sciences. Hence, the various implications of the study were discussed. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in the Health Field or Education)
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12 pages, 1249 KiB  
Article
Comparative Analysis of Artificial Intelligence Virtual Assistant and Large Language Models in Post-Operative Care
by Sahar Borna, Cesar A. Gomez-Cabello, Sophia M. Pressman, Syed Ali Haider, Ajai Sehgal, Bradley C. Leibovich, Dave Cole and Antonio Jorge Forte
Eur. J. Investig. Health Psychol. Educ. 2024, 14(5), 1413-1424; https://doi.org/10.3390/ejihpe14050093 - 15 May 2024
Cited by 3 | Viewed by 1575
Abstract
In postoperative care, patient education and follow-up are pivotal for enhancing the quality of care and satisfaction. Artificial intelligence virtual assistants (AIVA) and large language models (LLMs) like Google BARD and ChatGPT-4 offer avenues for addressing patient queries using natural language processing (NLP) [...] Read more.
In postoperative care, patient education and follow-up are pivotal for enhancing the quality of care and satisfaction. Artificial intelligence virtual assistants (AIVA) and large language models (LLMs) like Google BARD and ChatGPT-4 offer avenues for addressing patient queries using natural language processing (NLP) techniques. However, the accuracy and appropriateness of the information vary across these platforms, necessitating a comparative study to evaluate their efficacy in this domain. We conducted a study comparing AIVA (using Google Dialogflow) with ChatGPT-4 and Google BARD, assessing the accuracy, knowledge gap, and response appropriateness. AIVA demonstrated superior performance, with significantly higher accuracy (mean: 0.9) and lower knowledge gap (mean: 0.1) compared to BARD and ChatGPT-4. Additionally, AIVA’s responses received higher Likert scores for appropriateness. Our findings suggest that specialized AI tools like AIVA are more effective in delivering precise and contextually relevant information for postoperative care compared to general-purpose LLMs. While ChatGPT-4 shows promise, its performance varies, particularly in verbal interactions. This underscores the importance of tailored AI solutions in healthcare, where accuracy and clarity are paramount. Our study highlights the necessity for further research and the development of customized AI solutions to address specific medical contexts and improve patient outcomes. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in the Health Field or Education)
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14 pages, 1850 KiB  
Article
Integration and Assessment of ChatGPT in Medical Case Reporting: A Multifaceted Approach
by Kuan-Chen Lin, Tsung-An Chen, Ming-Hwai Lin, Yu-Chun Chen and Tzeng-Ji Chen
Eur. J. Investig. Health Psychol. Educ. 2024, 14(4), 888-901; https://doi.org/10.3390/ejihpe14040057 - 30 Mar 2024
Cited by 2 | Viewed by 2146
Abstract
ChatGPT, a large language model, has gained significance in medical writing, particularly in case reports that document the course of an illness. This article explores the integration of ChatGPT and how ChatGPT shapes the process, product, and politics of medical writing in the [...] Read more.
ChatGPT, a large language model, has gained significance in medical writing, particularly in case reports that document the course of an illness. This article explores the integration of ChatGPT and how ChatGPT shapes the process, product, and politics of medical writing in the real world. We conducted a bibliometric analysis on case reports utilizing ChatGPT and indexed in PubMed, encompassing publication information. Furthermore, an in-depth analysis was conducted to categorize the applications and limitations of ChatGPT and the publication trend of application categories. A total of 66 case reports utilizing ChatGPT were identified, with a predominant preference for the online version and English input by the authors. The prevalent application categories were information retrieval and content generation. Notably, this trend remained consistent across different months. Within the subset of 32 articles addressing ChatGPT limitations in case report writing, concerns related to inaccuracies and a lack of clinical context were prominently emphasized. This pointed out the important role of clinical thinking and professional expertise, representing the foundational tenets of medical education, while also accentuating the distinction between physicians and generative artificial intelligence. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in the Health Field or Education)
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13 pages, 937 KiB  
Article
Examining Students’ Acceptance and Use of ChatGPT in Saudi Arabian Higher Education
by Abu Elnasr E. Sobaih, Ibrahim A. Elshaer and Ahmed M. Hasanein
Eur. J. Investig. Health Psychol. Educ. 2024, 14(3), 709-721; https://doi.org/10.3390/ejihpe14030047 - 17 Mar 2024
Cited by 5 | Viewed by 3873
Abstract
This study examines students’ acceptance and use of ChatGPT in Saudi Arabian (SA) higher education, where there is growing interest in the use of this tool since its inauguration in 2022. Quantitative research data, through a self-reporting survey drawing on the “Unified Theory [...] Read more.
This study examines students’ acceptance and use of ChatGPT in Saudi Arabian (SA) higher education, where there is growing interest in the use of this tool since its inauguration in 2022. Quantitative research data, through a self-reporting survey drawing on the “Unified Theory of Acceptance and Use of Technology” (UTAUT2), were collected from 520 students in one of the public universities in SA at the start of the first semester of the study year 2023–2024. The findings of structural equation modeling partially supported the UTAUT and previous research in relation to the significant direct effect of performance expectancy (PE), social influence (SI), and effort expectancy (EE) on behavioral intention (BI) on the use of ChatGPT and the significant direct effect of PE, SI, and BI on actual use of ChatGPT. Nonetheless, the results did not support earlier research in relation to the direct relationship between facilitating conditions (FCs) and both BI and actual use of ChatGPT, which was found to be negative in the first relationship and insignificant in the second one. These findings were because of the absence of resources, support, and aid from external sources in relation to the use of ChatGPT. The results showed partial mediation of BI in the link between PE, SI, and FC and actual use of ChatGPT in education and a full mediation in the link of BI between EE and actual use of ChatGPT in education. The findings provide numerous implications for scholars and higher education institutions in SA, which are also of interest to other institutions in similar contexts. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in the Health Field or Education)
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12 pages, 1689 KiB  
Article
ChatGPT’s Response Consistency: A Study on Repeated Queries of Medical Examination Questions
by Paul F. Funk, Cosima C. Hoch, Samuel Knoedler, Leonard Knoedler, Sebastian Cotofana, Giuseppe Sofo, Ali Bashiri Dezfouli, Barbara Wollenberg, Orlando Guntinas-Lichius and Michael Alfertshofer
Eur. J. Investig. Health Psychol. Educ. 2024, 14(3), 657-668; https://doi.org/10.3390/ejihpe14030043 - 8 Mar 2024
Cited by 8 | Viewed by 2398
Abstract
(1) Background: As the field of artificial intelligence (AI) evolves, tools like ChatGPT are increasingly integrated into various domains of medicine, including medical education and research. Given the critical nature of medicine, it is of paramount importance that AI tools offer a high [...] Read more.
(1) Background: As the field of artificial intelligence (AI) evolves, tools like ChatGPT are increasingly integrated into various domains of medicine, including medical education and research. Given the critical nature of medicine, it is of paramount importance that AI tools offer a high degree of reliability in the information they provide. (2) Methods: A total of n = 450 medical examination questions were manually entered into ChatGPT thrice, each for ChatGPT 3.5 and ChatGPT 4. The responses were collected, and their accuracy and consistency were statistically analyzed throughout the series of entries. (3) Results: ChatGPT 4 displayed a statistically significantly improved accuracy with 85.7% compared to that of 57.7% of ChatGPT 3.5 (p < 0.001). Furthermore, ChatGPT 4 was more consistent, correctly answering 77.8% across all rounds, a significant increase from the 44.9% observed from ChatGPT 3.5 (p < 0.001). (4) Conclusions: The findings underscore the increased accuracy and dependability of ChatGPT 4 in the context of medical education and potential clinical decision making. Nonetheless, the research emphasizes the indispensable nature of human-delivered healthcare and the vital role of continuous assessment in leveraging AI in medicine. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in the Health Field or Education)
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16 pages, 308 KiB  
Article
Drivers and Consequences of ChatGPT Use in Higher Education: Key Stakeholder Perspectives
by Ahmed M. Hasanein and Abu Elnasr E. Sobaih
Eur. J. Investig. Health Psychol. Educ. 2023, 13(11), 2599-2614; https://doi.org/10.3390/ejihpe13110181 - 9 Nov 2023
Cited by 38 | Viewed by 15656
Abstract
The incorporation of artificial intelligence (AI) into education has heralded a transformative era in the way students learn and faculties teach. Among the burgeoning array of AI tools, ChatGPT stands out as a versatile and powerful resource. Developed by OpenAI, ChatGPT is an [...] Read more.
The incorporation of artificial intelligence (AI) into education has heralded a transformative era in the way students learn and faculties teach. Among the burgeoning array of AI tools, ChatGPT stands out as a versatile and powerful resource. Developed by OpenAI, ChatGPT is an AI-driven conversational model that generates human-like responses. This research draws on the Constructivism Learning Theory to uncover the key drivers pushing higher education students to use ChatGPT for academic purposes, and the multifaceted consequences it brings to the academic environment, by integrating the perspectives of key stakeholders: students, faculty, and education experts/leaders. The key findings of in-depth, face-to-face, interviews with key stakeholders revealed 12 main drivers that motivate students and their faculty to use ChatGPT mainly for learning purposes. However, the findings identified the multifaceted (six positive and another six negative) consequences of using ChatGPT for academic purposes. Recommendations for mitigating the negative consequences of ChatGPT were discussed with key stakeholders, particularly education experts/leaders, who were more concerned about using ChatGPT for academic reasons. The research reveals that higher education institutions should establish clear guidelines as a part of higher education policy, supplemented with training sessions for students and their faculty, about the responsible use of ChatGPT for academic purposes to mitigate any ethical concerns. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in the Health Field or Education)
24 pages, 8344 KiB  
Article
Assessing the Usability of ChatGPT for Formal English Language Learning
by Sarang Shaikh, Sule Yildirim Yayilgan, Blanka Klimova and Marcel Pikhart
Eur. J. Investig. Health Psychol. Educ. 2023, 13(9), 1937-1960; https://doi.org/10.3390/ejihpe13090140 - 21 Sep 2023
Cited by 41 | Viewed by 13965
Abstract
Recently, the emerging technologies have been constantly shaping the education domain, especially the use of artificial intelligence (AI) for language learning, which has attracted significant attention. Many of the AI tools are being used for learning foreign languages, in both formal and informal [...] Read more.
Recently, the emerging technologies have been constantly shaping the education domain, especially the use of artificial intelligence (AI) for language learning, which has attracted significant attention. Many of the AI tools are being used for learning foreign languages, in both formal and informal ways. There are many studies that have explored the potential of the recent technology “ChatGPT” for education and learning languages, but none of the existing studies have conducted any exploratory study for assessing the usability of ChatGPT. This paper conducts an assessment for usability of ChatGPT for formal English language learning. The study uses a standard questionnaire-based approach to ask participants about their feedback for usefulness and effectiveness of ChatGPT. The participants were asked for their feedback after performing series of tasks related to formal English language learning with ChatGPT. A variety of student participants were selected for this study with diverse English language proficiency levels, education levels, and nationalities. The quantitative analysis of the participant responses shed light on their experience with regards to the usability of ChatGPT for performing different English language learning tasks such as conversation, writing, grammar, and vocabulary. The findings from this study are quite promising and indicate that ChatGPT is an effective tool to be used for formal English language learning. Overall, this study contributes to the fast-growing research domain on using emerging technologies for formal English language learning by conducting in-depth assessment of usability for ChatGPT in formal English language learning. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in the Health Field or Education)
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15 pages, 1773 KiB  
Review
Artificial Intelligence Algorithms for Expert Identification in Medical Domains: A Scoping Review
by Sahar Borna, Barbara A. Barry, Svetlana Makarova, Yogesh Parte, Clifton R. Haider, Ajai Sehgal, Bradley C. Leibovich and Antonio Jorge Forte
Eur. J. Investig. Health Psychol. Educ. 2024, 14(5), 1182-1196; https://doi.org/10.3390/ejihpe14050078 - 28 Apr 2024
Cited by 1 | Viewed by 1616
Abstract
With abundant information and interconnectedness among people, identifying knowledgeable individuals in specific domains has become crucial for organizations. Artificial intelligence (AI) algorithms have been employed to evaluate the knowledge and locate experts in specific areas, alleviating the manual burden of expert profiling and [...] Read more.
With abundant information and interconnectedness among people, identifying knowledgeable individuals in specific domains has become crucial for organizations. Artificial intelligence (AI) algorithms have been employed to evaluate the knowledge and locate experts in specific areas, alleviating the manual burden of expert profiling and identification. However, there is a limited body of research exploring the application of AI algorithms for expert finding in the medical and biomedical fields. This study aims to conduct a scoping review of existing literature on utilizing AI algorithms for expert identification in medical domains. We systematically searched five platforms using a customized search string, and 21 studies were identified through other sources. The search spanned studies up to 2023, and study eligibility and selection adhered to the PRISMA 2020 statement. A total of 571 studies were assessed from the search. Out of these, we included six studies conducted between 2014 and 2020 that met our review criteria. Four studies used a machine learning algorithm as their model, while two utilized natural language processing. One study combined both approaches. All six studies demonstrated significant success in expert retrieval compared to baseline algorithms, as measured by various scoring metrics. AI enhances expert finding accuracy and effectiveness. However, more work is needed in intelligent medical expert retrieval. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in the Health Field or Education)
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14 pages, 906 KiB  
Review
Artificial-Intelligence-Based Clinical Decision Support Systems in Primary Care: A Scoping Review of Current Clinical Implementations
by Cesar A. Gomez-Cabello, Sahar Borna, Sophia Pressman, Syed Ali Haider, Clifton R. Haider and Antonio J. Forte
Eur. J. Investig. Health Psychol. Educ. 2024, 14(3), 685-698; https://doi.org/10.3390/ejihpe14030045 - 13 Mar 2024
Cited by 4 | Viewed by 5620
Abstract
Primary Care Physicians (PCPs) are the first point of contact in healthcare. Because PCPs face the challenge of managing diverse patient populations while maintaining up-to-date medical knowledge and updated health records, this study explores the current outcomes and effectiveness of implementing Artificial Intelligence-based [...] Read more.
Primary Care Physicians (PCPs) are the first point of contact in healthcare. Because PCPs face the challenge of managing diverse patient populations while maintaining up-to-date medical knowledge and updated health records, this study explores the current outcomes and effectiveness of implementing Artificial Intelligence-based Clinical Decision Support Systems (AI-CDSSs) in Primary Healthcare (PHC). Following the PRISMA-ScR guidelines, we systematically searched five databases, PubMed, Scopus, CINAHL, IEEE, and Google Scholar, and manually searched related articles. Only CDSSs powered by AI targeted to physicians and tested in real clinical PHC settings were included. From a total of 421 articles, 6 met our criteria. We found AI-CDSSs from the US, Netherlands, Spain, and China whose primary tasks included diagnosis support, management and treatment recommendations, and complication prediction. Secondary objectives included lessening physician work burden and reducing healthcare costs. While promising, the outcomes were hindered by physicians’ perceptions and cultural settings. This study underscores the potential of AI-CDSSs in improving clinical management, patient satisfaction, and safety while reducing physician workload. However, further work is needed to explore the broad spectrum of applications that the new AI-CDSSs have in several PHC real clinical settings and measure their clinical outcomes. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in the Health Field or Education)
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