Comparative accuracy of ChatGPT-4, Microsoft Copilot and Google Gemini in the Italian entrance test for healthcare sciences degrees: a cross-sectional study.

Artificial intelligence (AI) chatbots are emerging educational tools for students in healthcare science. However, assessing their accuracy is essential prior to adoption in educational settings. This study aimed to assess the accuracy of predicting the correct answers from three AI chatbots (ChatGPT-4, Microsoft Copilot and Google Gemini) in the Italian entrance standardized examination test of healthcare science degrees (CINECA test). Secondarily, we assessed the narrative coherence of the AI chatbots' responses (i.e., text output) based on three qualitative metrics: the logical rationale behind the chosen answer, the presence of information internal to the question, and presence of information external to the question. An observational cross-sectional design was performed in September of 2023. Accuracy of the three chatbots was evaluated for the CINECA test, where questions were formatted using a multiple-choice structure with a single best answer. The outcome is binary (correct or incorrect). Chi-squared test and a post hoc analysis with Bonferroni correction assessed differences among chatbots performance in accuracy. A p-value of < 0.05 was considered statistically significant. A sensitivity analysis was performed, excluding answers that were not applicable (e.g., images). Narrative coherence was analyzed by absolute and relative frequencies of correct answers and errors. Overall, of the 820 CINECA multiple-choice questions inputted into all chatbots, 20 questions were not imported in ChatGPT-4 (n = 808) and Google Gemini (n = 808) due to technical limitations. We found statistically significant differences in the ChatGPT-4 vs Google Gemini and Microsoft Copilot vs Google Gemini comparisons (p-value < 0.001). The narrative coherence of AI chatbots revealed "Logical reasoning" as the prevalent correct answer (n = 622, 81.5%) and "Logical error" as the prevalent incorrect answer (n = 40, 88.9%). Our main findings reveal that: (A) AI chatbots performed well; (B) ChatGPT-4 and Microsoft Copilot performed better than Google Gemini; and (C) their narrative coherence is primarily logical. Although AI chatbots showed promising accuracy in predicting the correct answer in the Italian entrance university standardized examination test, we encourage candidates to cautiously incorporate this new technology to supplement their learning rather than a primary resource. Not required.

Rossettini G ，Rodeghiero L ，Corradi F ，Cook C ，Pillastrini P ，Turolla A ，Castellini G ，Chiappinotto S ，Gianola S ，Palese A ... -  《BMC Medical Education》

Assessment of readability, reliability, and quality of ChatGPT®, BARD®, Gemini®, Copilot®, Perplexity® responses on palliative care.

There is no study that comprehensively evaluates data on the readability and quality of "palliative care" information provided by artificial intelligence (AI) chatbots ChatGPT®, Bard®, Gemini®, Copilot®, Perplexity®. Our study is an observational and cross-sectional original research study. In our study, AI chatbots ChatGPT®, Bard®, Gemini®, Copilot®, and Perplexity® were asked to present the answers of the 100 questions most frequently asked by patients about palliative care. Responses from each 5 AI chatbots were analyzed separately. This study did not involve any human participants. Study results revealed significant differences between the readability assessments of responses from all 5 AI chatbots (P < .05). According to the results of our study, when different readability indexes were evaluated holistically, the readability of AI chatbot responses was evaluated as Bard®, Copilot®, Perplexity®, ChatGPT®, Gemini®, from easy to difficult (P < .05). In our study, the median readability indexes of each of the 5 AI chatbots Bard®, Copilot®, Perplexity®, ChatGPT®, Gemini® responses were compared to the "recommended" 6th grade reading level. According to the results of our study answers of all 5 AI chatbots were compared with the 6th grade reading level, statistically significant differences were observed in the all formulas (P < .001). The answers of all 5 artificial intelligence robots were determined to be at an educational level well above the 6th grade level. The modified DISCERN and Journal of American Medical Association scores was found to be the highest in Perplexity® (P < .001). Gemini® responses were found to have the highest Global Quality Scale score (P < .001). It is emphasized that patient education materials should have a readability level of 6th grade level. Of the 5 AI chatbots whose answers about palliative care were evaluated, Bard®, Copilot®, Perplexity®, ChatGPT®, Gemini®, their current answers were found to be well above the recommended levels in terms of readability of text content. Text content quality assessment scores are also low. Both the quality and readability of texts should be brought to appropriate recommended limits.

Hancı V ，Ergün B ，Gül Ş ，Uzun Ö ，Erdemir İ ，Hancı FB ... -  《-》

Assessing the Readability of Patient Education Materials on Cardiac Catheterization From Artificial Intelligence Chatbots: An Observational Cross-Sectional Study.

Artificial intelligence (AI) is a burgeoning new field that has increased in popularity over the past couple of years, coinciding with the public release of large language model (LLM)-driven chatbots. These chatbots, such as ChatGPT, can be engaged directly in conversation, allowing users to ask them questions or issue other commands. Since LLMs are trained on large amounts of text data, they can also answer questions reliably and factually, an ability that has allowed them to serve as a source for medical inquiries. This study seeks to assess the readability of patient education materials on cardiac catheterization across four of the most common chatbots: ChatGPT, Microsoft Copilot, Google Gemini, and Meta AI. A set of 10 questions regarding cardiac catheterization was developed using website-based patient education materials on the topic. We then asked these questions in consecutive order to four of the most common chatbots: ChatGPT, Microsoft Copilot, Google Gemini, and Meta AI. The Flesch Reading Ease Score (FRES) was used to assess the readability score. Readability grade levels were assessed using six tools: Flesch-Kincaid Grade Level (FKGL), Gunning Fog Index (GFI), Coleman-Liau Index (CLI), Simple Measure of Gobbledygook (SMOG) Index, Automated Readability Index (ARI), and FORCAST Grade Level. The mean FRES across all four chatbots was 40.2, while overall mean grade levels for the four chatbots were 11.2, 13.7, 13.7, 13.3, 11.2, and 11.6 across the FKGL, GFI, CLI, SMOG, ARI, and FORCAST indices, respectively. Mean reading grade levels across the six tools were 14.8 for ChatGPT, 12.3 for Microsoft Copilot, 13.1 for Google Gemini, and 9.6 for Meta AI. Further, FRES values for the four chatbots were 31, 35.8, 36.4, and 57.7, respectively. This study shows that AI chatbots are capable of providing answers to medical questions regarding cardiac catheterization. However, the responses across the four chatbots had overall mean reading grade levels at the 11th-13th-grade level, depending on the tool used. This means that the materials were at the high school and even college reading level, which far exceeds the recommended sixth-grade level for patient education materials. Further, there is significant variability in the readability levels provided by different chatbots as, across all six grade-level assessments, Meta AI had the lowest scores and ChatGPT generally had the highest.

Behers BJ ，Vargas IA ，Behers BM ，Rosario MA ，Wojtas CN ，Deevers AC ，Hamad KM ... -  《Cureus》

Exploring the Performance of ChatGPT-4 in the Taiwan Audiologist Qualification Examination: Preliminary Observational Study Highlighting the Potential of AI Chatbots in Hearing Care.

Artificial intelligence (AI) chatbots, such as ChatGPT-4, have shown immense potential for application across various aspects of medicine, including medical education, clinical practice, and research. This study aimed to evaluate the performance of ChatGPT-4 in the 2023 Taiwan Audiologist Qualification Examination, thereby preliminarily exploring the potential utility of AI chatbots in the fields of audiology and hearing care services. ChatGPT-4 was tasked to provide answers and reasoning for the 2023 Taiwan Audiologist Qualification Examination. The examination encompassed six subjects: (1) basic auditory science, (2) behavioral audiology, (3) electrophysiological audiology, (4) principles and practice of hearing devices, (5) health and rehabilitation of the auditory and balance systems, and (6) auditory and speech communication disorders (including professional ethics). Each subject included 50 multiple-choice questions, with the exception of behavioral audiology, which had 49 questions, amounting to a total of 299 questions. The correct answer rates across the 6 subjects were as follows: 88% for basic auditory science, 63% for behavioral audiology, 58% for electrophysiological audiology, 72% for principles and practice of hearing devices, 80% for health and rehabilitation of the auditory and balance systems, and 86% for auditory and speech communication disorders (including professional ethics). The overall accuracy rate for the 299 questions was 75%, which surpasses the examination's passing criteria of an average 60% accuracy rate across all subjects. A comprehensive review of ChatGPT-4's responses indicated that incorrect answers were predominantly due to information errors. ChatGPT-4 demonstrated a robust performance in the Taiwan Audiologist Qualification Examination, showcasing effective logical reasoning skills. Our results suggest that with enhanced information accuracy, ChatGPT-4's performance could be further improved. This study indicates significant potential for the application of AI chatbots in audiology and hearing care services.

Wang S ，Mo C ，Chen Y ，Dai X ，Wang H ，Shen X ... -  《-》

Can artificial intelligence models serve as patient information consultants in orthodontics?

To evaluate the accuracy, reliability, quality, and readability of responses generated by ChatGPT-3.5, ChatGPT-4, Gemini, and Copilot in relation to orthodontic clear aligners. Frequently asked questions by patients/laypersons about clear aligners on websites were identified using the Google search tool and these questions were posed to ChatGPT-3.5, ChatGPT-4, Gemini, and Copilot AI models. Responses were assessed using a five-point Likert scale for accuracy, the modified DISCERN scale for reliability, the Global Quality Scale (GQS) for quality, and the Flesch Reading Ease Score (FRES) for readability. ChatGPT-4 responses had the highest mean Likert score (4.5 ± 0.61), followed by Copilot (4.35 ± 0.81), ChatGPT-3.5 (4.15 ± 0.75) and Gemini (4.1 ± 0.72). The difference between the Likert scores of the chatbot models was not statistically significant (p > 0.05). Copilot had a significantly higher modified DISCERN and GQS score compared to both Gemini, ChatGPT-4 and ChatGPT-3.5 (p < 0.05). Gemini's modified DISCERN and GQS score was statistically higher than ChatGPT-3.5 (p < 0.05). Gemini also had a significantly higher FRES compared to both ChatGPT-4, Copilot and ChatGPT-3.5 (p < 0.05). The mean FRES was 38.39 ± 11.56 for ChatGPT-3.5, 43.88 ± 10.13 for ChatGPT-4 and 41.72 ± 10.74 for Copilot, indicating that the responses were difficult to read according to the reading level. The mean FRES for Gemini is 54.12 ± 10.27, indicating that Gemini's responses are more readable than other chatbots. All chatbot models provided generally accurate, moderate reliable and moderate to good quality answers to questions about the clear aligners. Furthermore, the readability of the responses was difficult. ChatGPT, Gemini and Copilot have significant potential as patient information tools in orthodontics, however, to be fully effective they need to be supplemented with more evidence-based information and improved readability.

Dursun D ，Bilici Geçer R 《BMC Medical Informatics and Decision Making》