ChatGPT in medical imaging higher education

Currie, Geoffrey; Singh, Chandralekha; Nelson, Timothy S.; Nabasenja, Caroline; Al-Hayek, Yazan; Spuur, Kelly

doi:10.1016/j.radi.2023.05.011

Cited by 72 publications

(36 citation statements)

References 1 publication

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“…Echoing Currie et al's observations, our study also noted GPT-4's variable accuracy in diagnosing complex cardiac conditions, January 2024. Highlighting the critical role of contextual knowledge and expertise in medical diagnostics (27). Finally, in comparison to highly specialized and research-oriented deep learning tools, our results show lower accuracy.…”

Section: Discussionmentioning

confidence: 75%

Beyond Text: The Impact of Clinical Context on GPT-4’s 12-lead ECG Interpretation Accuracy

Lisicic,

Jordan,

Serman

et al. 2024

Preprint

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Introduction Artificial intelligence (AI) and large language models (LLMs), such as OpenAI's Chat Generative Pre-trained Transformer – version 4 (GPT-4), are being increasingly explored for medical applications, including clinical decision support. The introduction of the capability to analyze graphical inputs marks a significant advancement in the functionality of GPT-4. Despite the promising potential of AI in enhancing diagnostic accuracy, the effectiveness of GPT-4 in interpreting complex 12-lead electrocardiograms (ECGs) remains to be assessed. Methods This study utilized GPT-4 to interpret 150 12-lead ECGs from the Cardiology Research Dubrava (CaRD) registry, spanning a wide range of cardiac pathologies. The ECGs were classified into four categories for analysis: Arrhythmias (Category 1), Conduction System abnormalities (Category 2), Acute Coronary Syndrome (Category 3), and Other (Category 4). Two experiments were conducted: one where GPT-4 interpreted ECGs without clinical context and another with added clinical scenarios. A panel of experienced cardiologists evaluated the accuracy of GPT-4's interpretations. Statistical significance was determined using the Shapiro-Wilk test for distribution, Mann-Whitney U test for continuous variables, and Chi-square/Fisher's exact tests for categorical variables. Results In this cross-sectional, observational study, GPT-4 demonstrated a correct interpretation rate of 19% without clinical context and a significantly improved rate of 45% with context (p < 0.001). The addition of clinical scenarios significantly enhanced interpretative accuracy, particularly in the Category 3 (Acute Coronary Syndrome) (10 vs. 70%, p < 0.0.01). Unlike Category 4 (Other) which showed no impact (51 vs. 59%, p = 0.640), an impact with a trend toward significance was observed in Category 1 (Arrhythmias) (9.7 vs. 32%, p = 0.059) and Category 2 (Conduction System abnormalities) (4.8 vs. 19%, p = 0.088) when tasked with context. Conclusion While GPT-4 shows some potential in aiding ECG interpretation, its effectiveness varies significantly depending on the presence of clinical context. The study suggests that, in its current form, GPT-4 alone may not suffice for accurate ECG interpretation across a broad spectrum of cardiac conditions.

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Section: Discussionmentioning

confidence: 75%

Beyond Text: The Impact of Clinical Context on GPT-4’s 12-lead ECG Interpretation Accuracy

Lisicic,

Jordan,

Serman

et al. 2024

Preprint

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“…Numerous publications thereafter examined the LLM’s limitations that had been already identified by the students: incorrect answers and outdated content [ 10 ] possibly due to its limited data set [ 37 , 38 , 43 ], the possibility for fabricated information and hallucination [ 44 ], false citations and links leading to nonexistent sources [ 38 , 44 , 45 ], inability to browse the web [ 41 ], and risks for plagiarism [ 3 , 46 ].…”

Section: Discussionmentioning

confidence: 99%

Evaluation of ChatGPT’s Real-Life Implementation in Undergraduate Dental Education: Mixed Methods Study

Kavadella,

Dias da Silva,

Kaklamanos

et al. 2024

JMIR Med Educ

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Background The recent artificial intelligence tool ChatGPT seems to offer a range of benefits in academic education while also raising concerns. Relevant literature encompasses issues of plagiarism and academic dishonesty, as well as pedagogy and educational affordances; yet, no real-life implementation of ChatGPT in the educational process has been reported to our knowledge so far. Objective This mixed methods study aimed to evaluate the implementation of ChatGPT in the educational process, both quantitatively and qualitatively. Methods In March 2023, a total of 77 second-year dental students of the European University Cyprus were divided into 2 groups and asked to compose a learning assignment on “Radiation Biology and Radiation Protection in the Dental Office,” working collaboratively in small subgroups, as part of the educational semester program of the Dentomaxillofacial Radiology module. Careful planning ensured a seamless integration of ChatGPT, addressing potential challenges. One group searched the internet for scientific resources to perform the task and the other group used ChatGPT for this purpose. Both groups developed a PowerPoint (Microsoft Corp) presentation based on their research and presented it in class. The ChatGPT group students additionally registered all interactions with the language model during the prompting process and evaluated the final outcome; they also answered an open-ended evaluation questionnaire, including questions on their learning experience. Finally, all students undertook a knowledge examination on the topic, and the grades between the 2 groups were compared statistically, whereas the free-text comments of the questionnaires were thematically analyzed. Results Out of the 77 students, 39 were assigned to the ChatGPT group and 38 to the literature research group. Seventy students undertook the multiple choice question knowledge examination, and examination grades ranged from 5 to 10 on the 0-10 grading scale. The Mann-Whitney U test showed that students of the ChatGPT group performed significantly better (P=.045) than students of the literature research group. The evaluation questionnaires revealed the benefits (human-like interface, immediate response, and wide knowledge base), the limitations (need for rephrasing the prompts to get a relevant answer, general content, false citations, and incapability to provide images or videos), and the prospects (in education, clinical practice, continuing education, and research) of ChatGPT. Conclusions Students using ChatGPT for their learning assignments performed significantly better in the knowledge examination than their fellow students who used the literature research methodology. Students adapted quickly to the technological environment of the language model, recognized its opportunities and limitations, and used it creatively and efficiently. Implications for practice: the study underscores the adaptability of students to technological innovations including ChatGPT and its potential to enhance educational outcomes. Educators should consider integrating ChatGPT into curriculum design; awareness programs are warranted to educate both students and educators about the limitations of ChatGPT, encouraging critical engagement and responsible use.

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“…Adding to this reality, the recent emergence of AI-based language models, such as ChatGPT, Google Bard, Microsoft Bing Chat, among others, has triggered unprecedented interrogations to the world's higher education systems (Currie et al, 2023;Strzelecki, 2023). These inquiries are mainly centered around concomitant epistemological dilemmas (Benuyenah, 2023), their intertwining with strategies to foster student engagement (Fuchs, 2023), the development of personalized learning models (Lo, 2023), and the limitation of creative capacities (Gilson et al, 2023;Wang et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Bibliometric analysis of global scientific literature on the application and implementation of artificial intelligence in higher education

Espinoza-Hurtado,

Bastidas-Santivañez,

Sarmiento-Peralta

2024

Preprint

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This study aimed to analyze the bibliometric characteristics of global scientific literature on the application and implementation of artificial intelligence in higher education. A bibliometric study was conducted using a search strategy applied in Scopus. Productivity, visibility, and impact indicators were estimated using the SciVal tool. The majority of the world's scientific production on the subject belongs to the field of computer science and engineering. Additionally, high-impact journals play a significant role in dissemination. Articles published in recent years received higher citations. China and India have institutions actively contributing to productivity, although it is essential to strengthen international, inter-institutional, and interprofessional cooperation to promote and enhance the use of artificial intelligence in teaching and learning processes in higher education.

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ChatGPT in medical imaging higher education

Cited by 72 publications

References 1 publication

Beyond Text: The Impact of Clinical Context on GPT-4’s 12-lead ECG Interpretation Accuracy

Beyond Text: The Impact of Clinical Context on GPT-4’s 12-lead ECG Interpretation Accuracy

Evaluation of ChatGPT’s Real-Life Implementation in Undergraduate Dental Education: Mixed Methods Study

Bibliometric analysis of global scientific literature on the application and implementation of artificial intelligence in higher education

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