Correct Answer Rate Research Articles

Performance of ChatGPT-3.5 and ChatGPT-4o in the Japanese National Dental Examination.

In this study, we compared the performance of ChatGPT-3.5 to that of ChatGPT-4o in the context of the Japanese National Dental Examination, which assesses clinical reasoning skills and dental knowledge, to determine their potential usefulness in dental education. ChatGPT's performance was assessed using 1399 (55% of the exam) of 2520 questions from the Japanese National Dental Examinations (111-117). The 1121 excluded questions (45% of the exam) contained figures or tables that ChatGPT could not recognize. The questions were categorized into 18 different subjects based on dental specialty. Statistical analysis was performed using SPSS software, with McNemar's test applied to assess differences in performance. A significant improvement was noted in the percentage of correct answers from ChatGPT-4o (84.63%) compared with those from ChatGPT-3.5 (45.46%), demonstrating enhanced reliability and subject knowledge. ChatGPT-4o consistently outperformed ChatGPT-3.5 across all dental subjects, with significant improvements in subjects such as oral surgery, pathology, pharmacology, and microbiology. Heatmap analysis revealed that ChatGPT-4o provided more stable and higher correct answer rates, especially for complex subjects. This study found that advanced natural language processing models, such as ChatGPT-4o, potentially have sufficiently advanced clinical reasoning skills and dental knowledge to function as a supplementary tool in dental education and exam preparation.

The effect of calculus and kinematics contexts on students’ understanding of graphs

In this study, we compare students’ understanding of the derivative as slope and the antiderivative as the area under the curve using isomorphic graph-based problems in both calculus and kinematics contexts. Drawing from previous research, we designed two isomorphic tests, each with 12 items, and administered them to 543 university students. Our findings show that students performed significantly better on the kinematics test, with a higher rate of correct answers in some items. We also identified the most frequent errors and general trends in students’ selection of incorrect answers across both contexts. Based on these results, we provide specific recommendations for improving the instruction of these concepts. The analyses, recommendations, and tests included in the study can serve as valuable resources for mathematics and science education researchers and instructors teaching these topics. This study offers insights into how context influences students’ conceptual understanding, with implications for enhancing calculus and physics education.

간호대학생의 표준주의 지식과 인식, 간호전문직관이 감염관리 표준주의 수행도에 미치는 영향

The purpose of this study was to identify the factors influencing nursing students' performance of taking standard precautions and which is a descriptive research study. The subjects of the study were 163 students(3rd and 4th grade) with clinical practice experience. Data collection was conducted from September to December 2023, and SPSS/WIN 27.0 was used for the collected data. As a result of the study, the average knowledge level of the subjects about standard was 38.91 out of 42 points and the average correct answer rate was analyzed as 92.6%. The average of the awareness of standard precautions was 4.81 points out of 5 points, the nursing professionalism was 4.03 points out of 5 points, and the average of the performance was 4.45 points out of 5 points. The results of the performance of taking standard precautions according to general characteristics were significantly different from satisfaction with major and clinical practice. And awareness of standard precautions and the nursing professionalism had a significant positive correlation with performance of taking standard precautions The factors influencing the performance of taking standard precautions were awareness of standard precautions and the nursing professionalism, which showed 16.5% of explanatory power. In order to improve the performance of infection control standard precautionsof nursing students, education related to infection control awareness as well as application of programs that can improve nursing professionalism are needed.

Hypertension management: A comparative analysis of garlic, hibiscus, hawthorn, and olive leaf and a survey

Hypertension, a prevalent cardiovascular condition characterized by elevated blood pressure, poses a significant global health challenge. This paper reviews the potential of garlic, hibiscus, hawthorn, and olive leaf in reducing hypertension and improving one’s health. A survey was conducted among first year pharmacy students. The survey included 5 knowledge-based and 5 opinion-based questions, focusing on the four herbal remedies. The knowledge-based questions showed a correct answer rate of 61.1%, with the statement that garlic is generally safe to include in one’s diet, but excessive consumption can lead to adverse effects garnering a 91.1% correct response rate. 58.3% of the respondents failed to know the simple definition of hypertension. Opinion-based questions revealed a positive attitude towards herbal remedies with an average of 81% showing agreement on the potential benefits. Nearly 83% believed in consulting health professionals before integrating olive leaf extract, and about 89% agreed that garlic should be used as an approach to manage hypertension.

Anti-gingivitis natural products: Aloe vera gel, tea tree oil mouthwash, turmeric gel, myrrh extract/mouthwash

Gingivitis is an inflammatory gum disease which occurs around the cervical portion of the gum and is classified by its clinical appearance. Gingivitis is very common, and anyone can be affected including but not limited to poor oral care habits. This paper reviews the potential of Aloe Vera, Tea Tree Oil Mouthwash, Turmeric Gel, and Myrrh Extract/Mouthwash. The study also assessed the knowledge and opinions of first-year pharmacy students. The survey part of the study included 5 knowledge-based and 5 opinion-based questions, focusing on the four herbal remedies. The knowledge-based questions showed a 65.7% correct response rate, with the question on turmeric receiving the highest accuracy (94.3%), while the question surveying the participants’ knowledge about the source of information for herbal products received the lowest correct answer rate at 31.4%. Opinion-based questions revealed a positive attitude towards herbal remedies, with about 67.6% to 94.3% strongly agreeing, or agreeing with the potential benefits of the products. The highest agreement rate at 94.3% was obtained for the statement that myrrh can help reduce inflammation in the gums and inhibit the growth of bacteria, thus assisting in the management of gingivitis. Disagreement of opinions was minimal, ranging from 5.7% to 32.3%, indicating a widespread inclination towards positive agreement.

Human T-cell lymphotropic virus: knowledge of academics from a higher education institution

Objective: To estimate the knowledge of nursing students from two higher education institutions in relation to Human T-cell Lymphotropic Virus. Materials and Methods: This is a quantitative descriptive and cross-sectional study, conducted with nursing students from a higher education institution in Minas Gerais, in October 2023. In this work, it was decided to develop a data collection instrument, applied through an online questionnaire made available by the Google Forms platform. Results: A total of 91 questionnaires were received, of which 81 were validated, and it was observed that 70% of the students stated that they had no knowledge about this virus. However, in the specific questions about the Human T-Cell Lymphotropic Virus, the average rate of correct answers of 58.91% was tabulated and calculated. Conclusion: Thus, since these are future health professionals, this percentage is considered below what is necessary, so it is essential to have a greater involvement of this group with the theme, in order to improve the management of cases, avoiding greater transmissibility of the virus.

시뮬레이션 기반 평가에서 프로세스 데이터를 활용한 협력적 문제해결력 유형 분석

This study aims to identify the types and characteristics of collaborative problem-solving skills among test takers in South Korea. For this, process data from the PISA 2015 collaborative problem-solving assessment was analyzed using the K-medoids clustering method. The analysis revealed three distinct types of collaborative problem-solving skills: a fast type that allocates less time to responses, a deliberative type, and a type that engages in a higher number of interactions over a longer period, even when achievement levels are similar. We also analyzed the distribution of correct answer rates and collaborative problem-solving competency scores by cluster and level, confirming that various achievement levels were represented across all clusters. Based on these differences, educational and evaluative intervention strategies were explored, and the implications for assessment were discussed.

Comparative performance of artificial intelligence models in rheumatology board-level questions: evaluating Google Gemini and ChatGPT-4o.

This study evaluates the performance of AI models, ChatGPT-4o and Google Gemini, in answering rheumatology board-level questions, comparing their effectiveness, reliability, and applicability in clinical practice. A cross-sectional study was conducted using 420 rheumatology questions from the BoardVitals question bank, excluding 27 visual data questions. Both artificial intelligence models categorized the questions according to difficulty (easy, medium, hard) and answered them. In addition, the reliability of the answers was assessed by asking the questions a second time. The accuracy, reliability, and difficulty categorization of the AI models' response to the questions were analyzed. ChatGPT-4o answered 86.9% of the questions correctly, significantly outperforming Google Gemini's 60.2% accuracy (p < 0.001). When the questions were asked a second time, the success rate was 86.7% for ChatGPT-4o and 60.5% for Google Gemini. Both models mainly categorized questions as medium difficulty. ChatGPT-4o showed higher accuracy in various rheumatology subfields, notably in Basic and Clinical Science (p = 0.028), Osteoarthritis (p = 0.023), and Rheumatoid Arthritis (p < 0.001). ChatGPT-4o significantly outperformed Google Gemini in rheumatology board-level questions. This demonstrates the success of ChatGPT-4o in situations requiring complex and specialized knowledge related to rheumatological diseases. The performance of both AI models decreased as the question difficulty increased. This study demonstrates the potential of AI in clinical applications and suggests that its use as a tool to assist clinicians may improve healthcare efficiency in the future. Future studies using real clinical scenarios and real board questions are recommended. Key Points •ChatGPT-4o significantly outperformed Google Gemini in answering rheumatology board-level questions, achieving 86.9% accuracy compared to Google Gemini's 60.2%. •For both AI models, the correct answer rate decreased as the question difficulty increased. •The study demonstrates the potential for AI models to be used in clinical practice as a tool to assist clinicians and improve healthcare efficiency.

A Pilot Study of the Computerized Brief Smell Identification Test

Objectives: A self-administered Computerized Brief Smell Identification Test (cB-SIT) was developed recently to perform the olfactory identification test under computer control. The aim of this study was to evaluate the clinical applicability of the cB-SIT as compared with the traditional Brief Smell Identification Test (B-SIT). Methods: Sixty healthy volunteers with self-reported normal olfactory function, 30 hyposmic patients, and 30 anosmic patients were enrolled from June 2023 to May 2024. All enrolled participants received both B-SIT and cB-SIT in a random order to measure their odor identification ability. Thirty healthy volunteers took the second B-SIT and cB-SIT at least one week later. Results: The score was significantly different in both B-SIT and cB-SIT among healthy volunteers, hyposmic, and anosmic patients. The correct answer rate was significantly different in 10 items of the B-SIT and in 7 items of the cB-SIT among the three groups, but the post hoc test showed significant differences in correct answer rates between healthy volunteers and hyposmic patients in 7 items of both the B-SIT and cB-SIT. Test–retest results showed the score of the second B-SIT test was significantly higher than that of the first test, but the scores of the two tests of the cB-SIT were not significantly different. In the B-SIT, the lemon odorant had a higher correct answer rate in the second test than in the first test, but in the cB-SIT, the correct answer rate was not significantly different between the first and second tests in all 12 items. Conclusions: Our findings demonstrate that the cB-SIT was similar to the B-SIT and can be administered in the diagnosis of patients with olfactory dysfunction.

Desempenho de escolares em textos lacunados com uso de figuras e palavras

The objective of this study was to verify the performance of students in the 2nd year of Elementary School in the use of text with pictures and text with words. The study included 21 students from the 2nd year of public education, without learning difficulties. The initial stage of the research proposed to carry out the adaptation of two texts. In the first text, words were replaced by gaps to fill in, with the selection between two figures of the one that best represented the meaning of the sentence and, subsequently, the word was written in the gap. In the second text, words were removed and gaps were formed to be filled in with a written word, selected between two semantically different response options. In the next stage, the texts were applied in two individual sessions. As a result, there was an average of 6.95 out of a maximum of seven gaps in the first text and 8.3 out of a total of nine gaps for the second text. Reading time was longer at T2 compared to T1. In the classification of misunderstandings to fill in the gaps, most exchanges were identified as close co-hyponyms. Regarding spelling errors, the students had a higher number of errors in the first text compared to the second. It was concluded that it was possible to verify the performance of students in the 2nd year of Elementary School in the use of lacunated texts, both with images and words. The analysis of the answers by successes and errors helped in the reflection on the processes acquired in this educational phase and on measures that can help the learner, since the rate of correct answers was high.

Analysis of Responses of GPT-4V to the Japanese National Clinical Engineer Licensing Examination.

Chat Generative Pretrained Transformer (ChatGPT; OpenAI) is a state-of-the-art large language model that can simulate human-like conversations based on user input. We evaluated the performance of GPT-4V in the Japanese National Clinical Engineer Licensing Examination using 2,155 questions from 2012 to 2023. The average correct answer rate for all questions was 86.0%. In particular, clinical medicine, basic medicine, medical materials, biological properties, and mechanical engineering achieved a correct response rate of ≥ 90%. Conversely, medical device safety management, electrical and electronic engineering, and extracorporeal circulation obtained low correct answer rates ranging from 64.8% to 76.5%. The correct answer rates for questions that included figures/tables, required numerical calculation, figure/table ∩ calculation, and knowledge of Japanese Industrial Standards were 55.2%, 85.8%, 64.2% and 31.0%, respectively. The reason for the low correct answer rates is that ChatGPT lacked recognition of the images and knowledge of standards and laws. This study concludes that careful attention is required when using ChatGPT because several of its explanations lack the correct description.

Examining the competence of artificial intelligence programs in neuro-ophthalmological disorders and analyzing their comparative superiority

Abstract: BACKGROUND: This study aims to evaluate the knowledge levels of chat generative pretrained transformer (ChatGPT), Bing, and Bard programs, which are three different artificial intelligence chatbots offered to the market free of charge by various manufacturers, regarding neuro-ophthalmological diseases, to examine their usability, and to investigate the existence of their superiority to each other. MATERIALS AND METHODS: Forty questions related to neuro-ophthalmological diseases were obtained from the study questions’ section of the American Academy and Ophthalmology 2022–2023 Basic and Clinical Science Course Neuro-ophthalmology Book. The questions were posed to the ChatGPT, Bing, and Bard artificial intelligence chatbots. The answers were evaluated as correct or incorrect. The statistical relationship between the correct and incorrect answer rates offered by the artificial intelligence programs was tested. RESULTS: The correct answer rates were given by the artificial intelligence programs to the questions asked: ChatGPT – 52.5%; Bing – 55%; and Bard – 65%. There was no statistically significant difference between the correct answer rates of the three artificial intelligence programs (P = 0.489, Pearson’s Chi-square test). CONCLUSION: Although information about neuro-ophthalmological diseases can be accessed quickly and accurately using up-to-date artificial intelligence programs, the answers given may not always be correct. Care should always be taken when evaluating the answers to the questions.

Evaluating Large Language Models in Dental Anesthesiology: A Comparative Analysis of ChatGPT-4, Claude 3 Opus, and Gemini 1.0 on the Japanese Dental Society of Anesthesiology Board Certification Exam.

Purpose Large language models (LLMs) are increasingly employed across various fields, including medicine and dentistry. In the field of dental anesthesiology, LLM is expected to enhance the efficiency of information gathering, patient outcomes, and education. This study evaluates the performance of different LLMs in answering questions from the Japanese Dental Society of Anesthesiology Board Certification Examination (JDSABCE) to determine their utility in dental anesthesiology. Methods The study assessed three LLMs, ChatGPT-4 (OpenAI, San Francisco, California, United States), Gemini 1.0 (Google, Mountain View, California, United States), and Claude 3 Opus (Anthropic, San Francisco, California, United States), using multiple-choice questions from the 2020 to 2022 JDSABCE exams. Each LLM answered these questions three times. The study excluded questions involving figures or deemed inappropriate. The primary outcome was the accuracy rate of each LLM, with secondary analysis focusing on six subgroups: (1) basic physiology necessary for general anesthesia, (2) local anesthesia, (3) sedation and general anesthesia, (4) diseases and patient management methods that pose challenges in systemic management, (5) pain management, and (6) shock and cardiopulmonary resuscitation. Statistical analysis was performed using one-way ANOVA with Dunnett's multiple comparisons, with a significance threshold of p<0.05. Results ChatGPT-4 achieved a correct answer rate of 51.2% (95% CI: 42.78-60.56, p=0.003) and Claude 3 Opus 47.4% (95% CI: 43.45-51.44, p<0.001), both significantly higher than Gemini 1.0, which had a rate of 30.3% (95% CI: 26.53-34.14). In subgroup analyses, ChatGPT-4 and Claude 3 Opus demonstrated superior performance in basic physiology, sedation and general anesthesia, and systemic management challenges compared to Gemini 1.0. Notably, ChatGPT-4 excelled in questions related to systemic management (62.5%) and Claude 3 Opus in pain management (61.53%). Conclusions ChatGPT-4 and Claude 3 Opus exhibit potential for use in dental anesthesiology, outperforming Gemini 1.0. However, their current accuracy rates are insufficient for reliable clinical use.These findings have significant implications for dental anesthesiology practice and education, including educational support, clinical decision support, and continuing education. To enhance LLM utility in dental anesthesiology, it is crucial to increase the availability of high-quality information online and refine prompt engineering to better guide LLM responses.

Are Medical Students and Primary Health-care Professionals Aware of Neonatal Cholestasis and Acholic Stool.

Early diagnosis of biliary atresia (BA) and the timing of Kasai hepatic portoenterostomy are associated with improved survival rates of the native liver. Acholic stool is a major and earliest sign of BA. We evaluated the awareness and recognition of medical students and primary health care professionals (PHCPs) about neonatal cholestasis and acholic stool as a marker of BA. The knowledge of students and PHCP about prolonged jaundice and acholic stool was evaluated through a questionnaire. In the first step, 5 questions evaluating the knowledge of prolonged jaundice were asked. The sixth question was "Have you ever seen acholic stool before?" Following this question, stool color cards with 9 colors were shown, and participants were asked "Which of the following stool pictures would you define as acholic?" A total 724 students and 88 PHCPs were included in the study. In both groups, about half of the participants could not answer the first 4questions related to prolonged jaundice and cholestasis correctly. Twenty-four percent of the students and 11.4% of PHCP answered correctly to all of the stool colors. The rate of correct answers to acholic stool colors were approximately 43.9%-87.6% and 23.9%-86.4% for students and PHCP, respectively. Whitish acholic stool colors were better known than mild yellowish pale stool colors. The percentages of recognition were less than about 50% for these stool colors. This study showed that recognition and awareness of prolonged jaundice are low, and acholic stool is not well known. This may lead to delay in diagnosis. Considering the international success of stool color cards, using stool color cards will improve the outcomes of biliary atresia in our country as well.

Assessment Study of ChatGPT-3.5's Performance on the Final Polish Medical Examination: Accuracy in Answering 980 Questions.

The use of artificial intelligence (AI) in education is dynamically growing, and models such as ChatGPT show potential in enhancing medical education. In Poland, to obtain a medical diploma, candidates must pass the Medical Final Examination, which consists of 200 questions with one correct answer per question, is administered in Polish, and assesses students' comprehensive medical knowledge and readiness for clinical practice. The aim of this study was to determine how ChatGPT-3.5 handles questions included in this exam. This study considered 980 questions from five examination sessions of the Medical Final Examination conducted by the Medical Examination Center in the years 2022-2024. The analysis included the field of medicine, the difficulty index of the questions, and their type, namely theoretical versus case-study questions. The average correct answer rate achieved by ChatGPT for the five examination sessions hovered around 60% and was lower (p < 0.001) than the average score achieved by the examinees. The lowest percentage of correct answers was in hematology (42.1%), while the highest was in endocrinology (78.6%). The difficulty index of the questions showed a statistically significant correlation with the correctness of the answers (p = 0.04). Questions for which ChatGPT-3.5 provided incorrect answers had a lower (p < 0.001) percentage of correct responses. The type of questions analyzed did not significantly affect the correctness of the answers (p = 0.46). This study indicates that ChatGPT-3.5 can be an effective tool for assisting in passing the final medical exam, but the results should be interpreted cautiously. It is recommended to further verify the correctness of the answers using various AI tools.

Alignment of Patient Information Leaflets with the Health Literacy Skills of Future End-Users: Are We on the Same Page?

ABSTRACT Effective health communication will not be possible if the messages directed to patients do not adapt to their health literacy skills. In this sense, if the Patient Information Leaflets (PILs) are not understood properly, they will not fulfill their purpose. Secondary education aims to develop students’ fundamental skills, including reading comprehension, which should align with future patients. This study assesses reading comprehension of commonly used PILs among secondary education students. An observational cross-sectional study involved 590 Spanish secondary school students from March to June 2022. They read 3 original PILs and completed a questionnaire about medication use information. The European health literacy survey questionnaire (short version) and sociodemographic data were collected. The average correct answer rate was only 51%, with just 14.58% understanding when to take ibuprofen, results that fell significantly below the minimum 80% threshold required by the European Union. Age, gender, and cultural background didn’t significantly impact comprehension. In conclusion, health literacy skills acquired in secondary education are insufficient for understanding current PILs. Educational reform is necessary to improve students’ ability to comprehend medication instructions and enhance PILs for effective communication. At the same time, our work highlights that current PILs need to be redesigned to reduce the cognitive burden imposed on patients.

A Comparative Analysis of ChatGPT and Medical Faculty Graduates in Medical Specialization Exams: Uncovering the Potential of Artificial Intelligence in Medical Education.

Background This study aims to evaluate the performance of ChatGPT in the medical specialization exam (MSE) that medical graduates take when choosing their postgraduate specialization and to reveal how artificial intelligence-supported education can increase the quality and academic success of medical education. The research aims to explore the potential applications and advantages of artificial intelligence in medical education and examine ways in which this technology can contribute to student learning and exam preparation. Methodology A total of 240 MSE questions were posed to ChatGPT, 120 of which were basic medical sciences questions and 120 were clinical medical sciences questions. A total of 18,481 people participated in the exam. The performance of medical school graduates was compared with ChatGPT-3.5 in terms of answering these questions correctly. The average score for ChatGPT-3.5 was calculated by averaging the minimum and maximum scores. Calculations were done using the R.4.0.2 environment. Results The general average score of graduates was a minimum of 7.51 in basic sciences and a maximum of 81.46, while in clinical sciences, the average was a minimum of 12.51 and a maximum of 80.78. ChatGPT, on the other hand, had an average of at least 60.00 in basic sciences and a maximum of 72.00, with an average of at least 66.25 and a maximum of 77.00 in clinical sciences. The rate of correct answers in basic medical sciences for graduates was 43.03%, while for ChatGPT was 60.00%. In clinical medical sciences, the rate of correct answers for graduates was 53.29%, while for ChatGPT was 64.16%. ChatGPT performed best with a 91.66% correct answer rate in Obstetrics and Gynecology and an 86.36% correct answer rate in Medical Microbiology. The least successful area for ChatGPT was Anatomy, with a 28.00% correct answer rate, a subfield of basic medical sciences. Graduates outperformed ChatGPT in the Anatomy and Physiology subfields. Significant differences were found in all comparisons between ChatGPT and graduates. Conclusions This study shows that artificial intelligence models such as ChatGPT can provide significant advantages to graduates, as they score higher than medical school graduates. In terms of these benefits, recommended applications include interactive support, private lessons, learning material production, personalized learning plans, self-assessment, motivation boosting, and 24/7 access, among a variety of benefits. As a result, artificial intelligence-supported education can play an important role in improving the quality of medical education and increasing student success.

Testing the power of Google DeepMind: Gemini versus ChatGPT 4 facing a European ophthalmology examination

PurposeThe aim of this study was to compare the performances of Google Gemini and ChatGPT-4, facing a triple simulation of the European Board of Ophthalmologists (EBO) multiple choices exam. DesignObservational study. MethodsThe EBO multiple choice examination consists of 52 questions followed by 5 statements each, for a total of 260 answers. Statements may be answered with “True”, “False” or “Don't Know”: a correct answer is awarded 1 point; an incorrect is penalized 0.5 points; “don't know” scores 0 points. At least 60 % correct answers are needed to pass the exam. After explaining the rules to the chatbots, he entire question with the 5 statements was input. The rate of correct answers and the final score were collected. The exam simulation was repeated 3 times with randomly generated questions. ResultsGoogle Gemini and ChatGPT-4 succeed in EBO exam simulations in all 3 cases, with an average 85.3 ± 3.1 % and 83.3 ± 2.4 % of correct answers. Gemini had a lower error rate compared to ChatGPT (6.7 ± 1.5 % vs. 13.0 ± 2.6 %, p = 0.03), but answered “Don't know” more frequently (8.0 ± 2.7 % vs. 3.7 ± 1.5 %, p = 0.05). Both chatbots scored at least 70 % of correct answers in each exam subspecialty across the 3 simulations. Converting the percentages into points, Gemini scored 213.5 ± 9.3 points on average, compared to 199.8 ± 7.1 points for ChatGPT (p = 0.21). ConclusionsGoogle Gemini and ChatGPT-4 can both succeed in a complex ophthalmology examination on widespread topics, with higher accuracy compared to their former versions, highlighting their evolving importance in educational and informative setting. PrecisGoogle Gemini and ChatGPT-4 were both able to succeed in 3 consecutive exam simulations of the European Board of Ophthalmologists with an average of 85 % and 83 % correct answers, respectively. Google Gemini showed significantly less errors when compared to ChatGPT.

Depth estimation of pipe wall thinning using multifrequency reflection coefficients of T(0,1) mode-guided waves with supervised multilayer perceptron

This study entailed the development of a novel method for estimating the depth of wall thinning of pipes using multifrequency (30–65 kHz) reflection coefficients (MRCs) of the T(0,1) mode-guided waves and a multilayer perceptron (MLP). First, this study established why MRCs are a critical feature of the input layer of the MLP for the defect depth estimation of wall thinning. Further, a mathematical model that can quickly collect large amounts of training data was used to calculate the reflection waveforms. The depths of artificial and actual wall thinning were estimated using the MLP based on the MRCs and the mathematical model. Experiments were conducted using the T(0,1) mode-guided waves to obtain the MRCs for 21 artificial and 6 actual wall thinnings to estimate the defect depths. A maximum of 8347 training data points were prepared using the mathematical model. Because the optimization of the MLP strongly depended on the initial weights and biases, 100 random initial values were prepared to evaluate the average estimations and their standard deviations. The classification scheme of the MLP was used, with classification step widths of 0.5 and 0.25 mm. The correct answer rates for the 21 artificial defects were 93%, with a tolerance of ±0.5 mm for the 0.5 mm classification scheme; those for the 0.25 mm classification scheme were 89%. For the six actual defects, the correct answer rates were 100% with a tolerance of ±0.5 mm for both the 0.5 and 0.25 mm classification schemes. Sufficiently high correct answer rates were obtained in all the cases.

Evaluation of Current Artificial Intelligence Programs on the Knowledge of Glaucoma.

To measure the success of three different artificial intelligence chatbots, ChatGPT, Bard, and Bing, in correctly answering questions about glaucoma types and treatment modalities and to examine their superiority over each other. Thirty-two questions about glaucoma types and treatment modalities were asked using the ChatGPT, Bard, and Bing chatbots. The correct and incorrect answers were also provided. Accuracy rates were compared. Questions asked: ChatGPT answered 56.3%, Bard 78.1%, and Bing 59.4% correctly. There was no statistically significant difference between the three artificial intelligence chatbots in the rate of correct and incorrect answers to the questions asked (p = 0.195). Artificial intelligence chatbots can be used as a tool to access accurate information regarding glaucoma types and treatment modalities. However, the information obtained is not always accurate, and care should be taken when using this information.