Free Version Research Articles

Can ChatGPT Support Clinical Coding Using the ICD-10-CM/PCS?

Introduction: With the growing development and adoption of artificial intelligence in healthcare and across other sectors of society, various user-friendly and engaging tools to support research have emerged, such as chatbots, notably ChatGPT. Objective: To investigate the performance of ChatGPT as an assistant to medical coders using the ICD-10-CM/PCS. Methodology: We conducted a prospective exploratory study between 2023 and 2024 over 6 months. A total of 150 clinical cases coded using the ICD-10-CM/PCS, extracted from technical coding books, were systematically randomized. All cases were translated into Portuguese (the native language of the authors) and English (the native language of the ICD-10-CM/PCS). These clinical cases varied in complexity levels regarding the quantity of diagnoses and procedures, as well as the nature of the clinical information. Each case was input into the 2023 ChatGPT free version. The coding obtained from ChatGPT was analyzed by a senior medical auditor/coder and compared with the expected results. Results: Regarding the correct codes, ChatGPT’s performance was higher by approximately 29 percentage points between diagnoses and procedures, with greater proficiency in diagnostic codes. The accuracy rate for codes was similar across languages, with rates of 31.0% and 31.9%. The error rate in procedure codes was substantially higher than that in diagnostic codes by almost four times. For missing information, a higher incidence was observed in diagnoses compared to procedures of slightly more than double the comparative rates. Additionally, there was a statistically significant excess of codes not related to clinical information, which was higher in procedures and nearly the same value in both languages under study. Conclusion: Given the ease of access to these tools, this investigation serves as an awareness factor, demonstrating that ChatGPT can assist the medical coder in directed research. However, it does not replace their technical validation in this process. Therefore, further developments of this tool are necessary to increase the quality and reliability of the results.

Analisis Pengaruh Kelengkapan Produk dan Promosi Penjualan Terhadap Keputusan Pembelian Konsumen di Transmart KarawanG

The research was conducted at Transmart Karawang. In the current era of globalization, demand from consumers is increasing so as to provide profitable potential for the business world. A survey was conducted on the customer value index of 10 stores in Indonesia, one of the retail companies that is experiencing these problems is Transmart which occupies the fourth position. Reporting from kompas.com, it is said that at least 12 Transmart outlets will be permanently closed throughout 2022. The problem of declining sales levels at Transmart Karawang, as evidenced by the decreasing number of customers visiting the store, is the main subject of this study. This phenomenon is believed to arise due to consumer skepticism about their purchasing choices, which are influenced by product completeness and sales promotions. The purpose of this observation is to understand how product completeness and sales promotion affect consumer purchasing decisions at Transmart Karawang. Translated with DeepL.com (free version)The subjects of this research are consumers or customers of Transmart Karawang. The research methodology used quantitative and survey methodologies. The applied data sources include main data and supporting data, while the applied data collection techniques include questionnaires, face-to-face interactions, observations, and literature studies. A research sample of 99 respondents was selected from a population of 8422 using the Slovin formula. This research utilizes multiple linear regression analysis methodology using SPSS version 27.0 software to evaluate the effect of product completeness and sales promotion on purchasing decisions at Transmart Karawang. The research findings show that 82.9% of consumers in Transmart Karawang are influenced in their purchasing choices by the presence of product completeness and purchase promotions. A total of 17.1% of the evaluation was influenced by unresolved issues in this study.

A novel smart irrigation framework with timing allocation using solenoid valves and Arduino microcontroller

Irrigation in agriculture is the most common way of providing water to agricultural land or fields at normal stretches through channels and embedded platforms with the internet of things (IoT), to upgrade rural development. In this paper, the arrangement of the various types of irrigation systems and embedded platforms for agriculture was studied. The embedded platform can be designed in a suitable framework that can assist the irrigation system in growing more water-required crops. In this work, three relay switches, two solenoid valves, and one water pump source were connected to Arduino ESP32. The free version of Sinric Google Cloud was utilized significantly to control three devices namely, two solenoid valves using two relay switches and a water pump source using one relay switch. The experiment was executed in a prototype manner with timing allocation by considering two agricultural fields where water was supplied either in one field at a time and showed more prominent results to save time, replacement of manual valves, man intervention, power, and suitable quantity of water for more water-required crops namely, arecanut and coconut.

Analysis of School Financial Management in the Context of Tax Accounting: A Case Study at SMP Negeri 3 Hilisalawa'ahe

Schools as educational units manage their finances independently and are bound by tax obligations. Therefore, knowledge of tax accounting is very important in planning and implementing school activities and budgets. School principals, treasurers and BOS teams must understand tax regulations related to school revenues and expenditures; such as income tax (PPh), value-added tax (VAT) and local tax. With the above premise, the author is interested in conducting research on School Financial Management in the Context of Tax Accounting: Case Study at SMP Negeri 3 Hilisalawa'ahe. The purpose of this study is to describe financial management at SMP Negeri 3 Hilisalawa'ahe, analyze the suitability of its management for tax accounting provisions, identify the obstacles faced by the financial management team of SMP Negeri 3 Hilisalawa'ahe and formulate solutions to overcome these obstacles. This research uses a qualitative approach, which is a research procedure that produces descriptive data in the form of speech or writing and observable behavior of the person (subject) itself. The data collection methods used are observation, interviews, and document review with the object of research is the financial management of SMP Negeri 3 Hilisalawa'ahe. Based on the results of the study, it was found that the Financial Management and Reporting of SMP Negeri 3 Hilisalawa'ahe is in accordance with the general provisions and procedures of taxation and there are no obstacles faced in the financial management of SMP Negeri 3 Hilisalawa'ahe because the management team is in accordance with the professional field and understands tax regulations. Translated with DeepL.com (free version).

Political-organisational aspects for the prevention of genetic diseases

The explosive advances in medical genetics are, as is well known, very recent, but they already constitute major references in the preparation of the new models of health action postulated by the establishment of the national health service. They have made possible and at the same time necessitated extensive legislative and organisational design work for the prevention, diagnosis and treatment of genetic diseases. Translated with DeepL.com (free version)

Patient-friendliness of ChatGPT responses: NSCLC targeted therapy.

231 Background: Non-small cell lung cancer (NSCLC) targeted therapies are complex, often requiring extensive patient education beyond what can be conveyed in a single provider visit. Given the average US reading level is at the 8th grade, and many patients seek additional information online, it is vital to evaluate the readability of online resources. This study aims to determine the patient friendliness of information provided by AI chatbots like ChatGPT in explaining NSCLC targeted therapies compared to other commonly accessed sources. Methods: This analysis included targeted therapies approved by the FDA for EGFR-mutated NSCLC: Afatinib, Erlotinib, Osimertinib, Dacomitinib, and Gefitinib. Information sources included ChatGPT 4, ChatGPT 3.5, the Patient Information section of the FDA label, and the Google featured snippet. Each version of ChatGPT was queried 10 times for each individual therapy – “My doctor is suggesting starting therapy with (Drug Name). What can I expect with this medication?”. All responses, labels, and snippets were examined by Microsoft Word for word count (WC) and Flesch Reading Ease Score (FRES), which considers average sentence length and number of syllables per word to assess readability. Data analysis was performed using ANOVA in SAS. Results: Across all therapies, Mean FRES for ChatGPT 4 was 31.21, ChatGPT 3.5 26.69, FDA labels 50.78, and Google snippets 33.1. Mean WC for ChatGPT 4 was 312.54, ChatGPT 3.5 355.78, FDA labels 1220, and Google snippets 42. Significant differences in FRES were found among sources for Afatinib (p-value <0.0001), Erlotinib (p-value 0.0206), Osimertinib (p-value <0.0001), Dacomitinib (p-value 0.0125), and Gefitinib (p-value <0.0001). Significant differences in WC were also found among sources for Afatinib (p-value <0.0001), Erlotinib (p-value <0.0001), Osimertinib (p-value <0.0001), and Gefitinib (p-value 0.0045). No significant difference in WC was found for Dacomitinib (p-value 0.2807). Conclusions: While the FDA label provided the most readable information, none of the sources aligned with the average 8th-grade reading level in the US, indicating a gap in accessible patient education for NSCLC targeted therapies. Notably, readability varies significantly between ChatGPT versions, affecting accessibility for users of the free version, ChatGPT 3.5. Although ChatGPT responses are more succinct compared to the verbose FDA labels, their higher education-level readability presents a barrier to comprehension. This study highlights the need for further research into optimizing AI-generated patient education materials to be both accurate and comprehensible at appropriate reading levels, thereby improving health communication strategies.

EFFECTIVENESS OF DUOLINGO IN FOREIGN LANGUAGE LEARNING

This study aims to explore the efficiency of Duolingo as a language learning tool, with a particular focus on its gamified nature, adaptive learning technology and strategic use of notifications. In this regard, the study employed qualitative research design wherein two semi-structured interviews were held. Specifically, these participants were housewife who had been using Duolingo daily for almost 37 days to learn English and a student who was intermittently using it to learn Turkish. In conclusion, these findings show that apart from being interactive and engaging, Duolingo significantly improves vocabulary and grammar skills. Furthermore, such game-like features as rewards, competitions and streak counts act as strong incentives for continued usage. Additionally, customized messages delivered in real time can help in bringing back users into the application and ensuring daily routine learning is maintained. Nevertheless, despite its pros there are several cons that have been found; they include restriction of lives in free version and lack of practice realistic communication scenarios. Accordingly, researchers recommend introducing artificial intelligence for improved speaking practice and enhancing the number of lives to further improve the functionality of DuoLingo.com. These facts help give more insights on how digital tools can support language acquisition across diverse contexts. Key words: Duolingo, Language Learning, Gamification, Vocabulary, Grammar and Motivation.

La confección de la utopía comunitaria

The researchers who are part of this dossier are members of the Working Group on Anthropology of Communities, Futures and Utopias in Latin America, affiliated to the Latin American Anthropological Association (ALA), and of the Research Network on Communities, Utopias and Futures (RIOCOMUN). The studies and reflections contained in this dossier are nourished by the discussions provoked by meetings and dialogues that have been taking place in the network for more than three years. The texts strung together for this issue of Encartes show different historical and cultural contexts in different states of the country and abroad: Baja California, Jalisco, Michoacán, Veracruz, Chiapas; and in the north Patagonian region of Argentina. Translated with DeepL.com (free version)

Early insights into SLA with chatGPT: Navigating CS teachers and student perspectives in an opinion-based exploration

This study explores the integration of ChatGPT into Social Learning Analytics (SLA) to support programming education among computer science students at Mustapha Stambouli University, Mascara, Algeria. Utilizing a mixed-methods approach, the research combines quantitative surveys and qualitative analysis of recorded interactions of one example and interviews to examine the effectiveness, challenges, and perceptions of ChatGPT’s use in programming tasks across Arabic, French, and English. The study involved 57 students and five teachers, providing a comprehensive view of ChatGPT’s impact on learning experiences, engagement patterns, and programming performance. Results indicate that ChatGPT is frequently used as a supplementary tool, especially for programming-related queries, debugging, and last-minute assistance before deadlines. The tool’s adaptability to students’ needs, combined with its ease of use, enhances its perceived value in supporting independent learning. However, the limitations of the free version—such as restricted access, slower response times, and occasional inaccuracies—were frequently cited as barriers to consistent, effective use. Teachers acknowledged ChatGPT’s role in easing instructional burdens but emphasized the need for critical oversight to prevent over-reliance on AI-generated content. Ethical concerns regarding data privacy, academic integrity, and the quality of AI feedback were highlighted as key issues requiring attention. Interestingly, a significant portion of students expressed the belief that AI, including ChatGPT, could potentially replace human programmers in the near future, reflecting both optimism and concern about the evolving role of AI in the field. Despite this, educators maintained that while ChatGPT can augment programming education, human intuition, creativity, and contextual understanding remain irreplaceable. The study concludes that ChatGPT’s integration into SLA offers substantial opportunities to enhance educational support and enrich data on student learning behaviors. However, addressing accessibility issues, enhancing multilingual support, and mitigating ethical challenges are critical for maximizing the tool’s effectiveness. The findings underscore the importance of a balanced approach that leverages AI’s strengths while maintaining the essential role of human expertise in education and programming.

Predicting Long-Term Engagement in mHealth Apps: Comparative Study of Engagement Indices.

Digital health care apps, including digital therapeutics, have the potential to increase accessibility and improve patient engagement by overcoming the limitations of traditional facility-based medical treatments. However, there are no established tools capable of quantitatively measuring long-term engagement at present. This study aimed to evaluate an existing engagement index (EI) in a commercial health management app for long-term use and compare it with a newly developed EI. Participants were recruited from cancer survivors enrolled in a randomized controlled trial that evaluated the impact of mobile health apps on recovery. Of these patients, 240 were included in the study and randomly assigned to the Noom app (Noom Inc). The newly developed EI was compared with the existing EI, and a long-term use analysis was conducted. Furthermore, the new EI was evaluated based on adapted measurements from the Web Matrix Visitor Index, focusing on click depth, recency, and loyalty indices. The newly developed EI model outperformed the existing EI model in terms of predicting EI of a 6- to 9-month period based on the EI of a 3- to 6-month period. The existing model had a mean squared error of 0.096, a root mean squared error of 0.310, and an R2 of 0.053. Meanwhile, the newly developed EI models showed improved performance, with the best one achieving a mean squared error of 0.025, root mean squared error of 0.157, and R2 of 0.610. The existing EI exhibited significant associations: the click depth index (hazard ratio [HR] 0.49, 95% CI 0.29-0.84; P<.001) and loyalty index (HR 0.17, 95% CI 0.09-0.31; P<.001) were significantly associated with improved survival, whereas the recency index exhibited no significant association (HR 1.30, 95% CI 1.70-2.42; P=.41). Among the new EI models, the EI with a menu combination of menus available in the app's free version yielded the most promising result. Furthermore, it exhibited significant associations with the loyalty index (HR 0.32, 95% CI 0.16-0.62; P<.001) and the recency index (HR 0.47, 95% CI 0.30-0.75; P<.001). The newly developed EI model outperformed the existing model in terms of the prediction of long-term user engagement and compliance in a mobile health app context. We emphasized the importance of log data and suggested avenues for future research to address the subjectivity of the EI and incorporate a broader range of indices for comprehensive evaluation.

Pengaruh Tinggi Bukaan Katup terhadap Torsi dan Daya pada Motor Besin 4 Langkah Berkapasitas 200CC

Automobiles are now the primary mode of transportation due to rapid technological advancements. One method for accomplishing ideal volumetric effectiveness and augment power is to change the camshaft. This study means to grow understanding in the auto world in regards to power and force and to assess the impact of changes in camshaft lift level on a 200cc limit bike utilizing pertalite fuel. The information from the review is introduced in tables and examined utilizing the two-way ANOVA technique and charts. The results of the analysis indicate that a comparison of the power data obtained by adding the lift height (test 3) yields a result of 16 66 HP at 8500 RPM. In the mean time, the force information demonstrates the way that the force examination of the three tests can be supposed to be the most elevated information of the three tests, to be specific (test 3) which is completed by adding a high lift to get a force of 17 59 Nm at engine rotation 5000 RPM. Utilized DeepL.com (free version) for translation.

Fighting free with free: Freemium vs. Piracy

We analyze the optimal business model of a firm facing piracy. The firm either sells a premium version of its product, or also offers a free version along with the premium version. The firm can in turn impose restrictions on the use of the free version. Consumers can choose between the free and the premium version, but can also get an illegal digital copy. We show that freemium offers can reduce digital piracy by fighting free with free and that firms choose their optimal business model depending on the strength of copyright protection. Therefore, the strength of copyright protection can lead firms to choose a traditional business model rather than the new freemium model, impacting significantly the legal usage of the good.

L’utilité du facteur d’épissage SRSF1 dans le grading des tumeurs gliales: Une méta-analyse

The grading of glial tumors is based on morphological and sometimes on molecular features. Many markers have been assessed in order to grade the glial tumours without a real consensus. Some authors reported that SRSF1, a spiling factor, presents an expression correlated to the tumours grades. In this study, we aimed to assess the utility of the SRSF1 into the grading of gliomas based on its immunohistochemical expression. The authors conducted a meta-analysis under the PRISMA guidelines during a 10-year-period (2013-2023). The Meta-Disc software 5.4 (free version) was used. Q test and I2 statistics were carried out to explore the heterogeneity among studies. Meta-regression was performed in case of significant heterogeneity. Publication bias was assessed using the funnel plot test and the Egger's test (free version JASP). According to the inclusion criteria, 4 studies from 193 articles were included. The pooled SEN, SPE and DOR accounted respectively for 0.592, 0.565 and 1.852. The AUC was estimated to 0.558 suggesting a bad diagnostic accuracy. The heterogeneity in the pooled SEN and SPE was statistically significant. The meta-regression analysis focusing on the technique used, the clones, the dilution, the interpretation technique revealed no covariate factors (P>0.05). Even if this meta-analysis highlighted the absence of a real diagnostic utility of the SRSF1 in grading the glial tumours, the heterogeneity revealed reinforces the need for more prospective studies performed according to the quality assessment criteria.

The Potential Impact of Large Language Models on Doctor-Patient Communication: A Case Study in Prostate Cancer.

In recent years, the integration of large language models (LLMs) into healthcare has emerged as a revolutionary approach to enhancing doctor-patient communication, particularly in the management of diseases such as prostate cancer. Our paper evaluated the effectiveness of three prominent LLMs-ChatGPT (3.5), Gemini (Pro), and Co-Pilot (the free version)-against the official Romanian Patient's Guide on prostate cancer. Employing a randomized and blinded method, our study engaged eight medical professionals to assess the responses of these models based on accuracy, timeliness, comprehensiveness, and user-friendliness. The primary objective was to explore whether LLMs, when operating in Romanian, offer comparable or superior performance to the Patient's Guide, considering their potential to personalize communication and enhance the informational accessibility for patients. Results indicated that LLMs, particularly ChatGPT, generally provided more accurate and user-friendly information compared to the Guide. The findings suggest a significant potential for LLMs to enhance healthcare communication by providing accurate and accessible information. However, variability in performance across different models underscores the need for tailored implementation strategies. We highlight the importance of integrating LLMs with a nuanced understanding of their capabilities and limitations to optimize their use in clinical settings.

Can Chat-GPT read and understand guidelines? An example using the S2k guideline intrauterine growth restriction of the German Society for Gynecology and Obstetrics

PurposeTo investigate the capacity of chat-generative pre-trained transformer (Chat-GPT) to understand the S2k guideline of the German Society for Gynecology and Obstetrics on intrauterine growth restriction.MethodsThe German-language free Chat-GPT version was used to test the ability of Chat-GPT to understand the definition of small for gestational age and intrauterine growth restriction, to indicate the correct time and place of delivery and to evaluate ist ability to recommend a spontaneous delivery versus a primary caesarean section in accordance with the guideline recommendations. In order to objectively evaluate the suggestions a simple three-color ‘traffic light’ evaluation system was employed.ResultsAlmost all Chat-GPT’s suggestions in the context of definition of small for gestational age/intrauterine growth restriction as well as correct time of delivery were adequate, whereas more than half of the suggestions made in terms of correct delivery mode needed reformulation or even correction.ConclusionChat-GPT appears to be a valuable form of artificial intelligence that could be integrated into everyday clinical practice.

A Minkowski type inequality with free boundary in space forms

In this paper, we consider a Minkowski inequality for a domain supported on any totally umbilical hypersurface with free boundary in space forms. We generalize the main result in [32] into free boundary case and obtain a free boundary version of optimal weighted Minkowski inequality in space forms.

Comparative Analysis of Artificial Intelligence Chatbot Performance

Currently, Artificial Intelligence has penetrated almost every application and site on the Internet. This has had an impact on the world of education, business, etc. In addition to making it easier for humans to carry out their activities, this can also have negative effects if the response from the AI ​​chatbot is inaccurate or even misleading. In this article, the author has conducted experiments on several free versions of popular chatbots, namely ChatGPT, Gemini (Bard), AI Chat and Aichatting. AI chatbots are very helpful in the field of general knowledge, finding solutions to problems and creating creations, such as fiction, or guiding the creation of scientific reports. Users must understand and be observant in using this chatbot because the response is very dependent on the input given. Questions that contain errors will get different responses. All responses given by the AI ​​chatbot are suggestions, not something that must be followed absolutely. This is because the user is responsible for the consequences, not AI. AI has ethics in providing responses so that it will not produce negative answers or direct users to things that violate the rules. The factors that are the main measurements are speed, accuracy, completeness, understanding of questions, response variations, ability to handle input errors and ability to provide solutions. The four chatbots tested each have their own strengths and weaknesses, but there is one that has the most features and variations in its responses, namely Gemini (Bard).

IMPROVED DECISION-MAKING ALGORITHM FOR THE REDEVELOPMENT OF INDUSTRIAL AREAS

Raising of problem. As a result of the financial and economic crisis, many industrial enterprises have ceased operations or significantly reduced production volumes due to the shrinking markets for their products, which is accompanied by destructive processes and phenomena. In a dynamic competitive environment, some enterprises have outdated and worn-out fixed assets, their products are not in demand, their premises are leased, large areas are covered with waste and harmful substances that are environmentally hazardous, low technological level of production, weak scientific and technical sphere, and reduced supply of labour resources. Therefore, ensuring sustainable development of Ukraine is impossible without solving the problems of restructuring and qualitative renewal of industrial production, reconstruction of degraded urban areas occupied by abandoned buildings and structures of industrial enterprises. Thus, there is an objective need to increase the level of profitability of land development by justifying alternative land use options: demolition of degraded industrial enterprises and construction of new facilities or reconstruction of industrial buildings and structures with a change of functional purpose. However, there is currently no unified approach to building an information model of the decision-making process for the reconstruction of industrial enterprises with a change in their functional purpose. Translated with DeepL.com (free version). Purpose of the aricle. To develop an improved decision-making algorithm for the reconstruction of mining enterprises with a change in functional purpose. Conclusion. The decision-making algorithm for the reconstruction of industrial enterprises with a change in functional purpose, which ensures the receipt of substantiated values of technical and economic indicators of such projects, depending on the available initial information about the object and the conditions of production of works, and also provides the possibility of specifying the values indicators of the effectiveness of managerial decisions at different stages of the life cycle, thanks to the adjustment of the values of the duration and cost of reconstruction by varying the parameters that are part of the determining factors.

RECONSTRUCTION OF THE SYSTEM OF GREENING TERRITORIES OF THE DNIPRO AREA IN THE MINDS OF FURTHER TRANSFORMATIONS OF EXOGENIC, ENDOGENIC AND ANTHROPOGENIC FACTORS OF THE OLD DEVELOPMENT

Raising of problem. As a result of the financial and economic crisis, many industrial enterprises have ceased operations or significantly reduced production volumes due to the shrinking markets for their products, which is accompanied by destructive processes and phenomena. In a dynamic competitive environment, some enterprises have outdated and worn-out fixed assets, their products are not in demand, their premises are leased, large areas are covered with waste and harmful substances that are environmentally hazardous, low technological level of production, weak scientific and technical sphere, and reduced supply of labour resources. Therefore, ensuring sustainable development of Ukraine is impossible without solving the problems of restructuring and qualitative renewal of industrial production, reconstruction of degraded urban areas occupied by abandoned buildings and structures of industrial enterprises. Thus, there is an objective need to increase the level of profitability of land development by justifying alternative land use options: demolition of degraded industrial enterprises and construction of new facilities or reconstruction of industrial buildings and structures with a change of functional purpose. However, there is currently no unified approach to building an information model of the decision-making process for the reconstruction of industrial enterprises with a change in their functional purpose. Translated with DeepL.com (free version). Purpose of the aricle. To develop an improved decision-making algorithm for the reconstruction of mining enterprises with a change in functional purpose. Conclusion. The decision-making algorithm for the reconstruction of industrial enterprises with a change in functional purpose, which ensures the receipt of substantiated values of technical and economic indicators of such projects, depending on the available initial information about the object and the conditions of production of works, and also provides the possibility of specifying the values indicators of the effectiveness of managerial decisions at different stages of the life cycle, thanks to the adjustment of the values of the duration and cost of reconstruction by varying the parameters that are part of the determining factors.

ChatGPT sitting for FRCS Urology examination: Will artificial intelligence get certified?

Introduction: The use of artificial intelligence (AI), including neural networks and deep learning, has rapidly changed many industries. One recent application of AI that has gained the attention of physicians and the general public alike is ChatGPT, a chatbot developed and released by OpenAI Inc. in November2022. We challenged ChatGPT to sit the Fellowship of the Royal College of Surgeons (FRCS) Urology examination, both parts, to assess its performance and determine its eligibility for the title. Methods: We prepared a set of 100 Multiple-Choice Questions (MCQs) for Part 1 and 8 viva scenarios for Part 2. We choose to use ChatGPT 3.5 that is the free version available online, and responses were documented during the simulation. Results: In Part 1 MCQs, Chat Generative Pre-trained Transformer (ChatGPT) managed to answer some questions correctly with an overall score of 35%. However, in Part 2 Viva, its performance improved to an extent, demonstrating proficiency by offering detailed explanations and reasoning, achieving average score in some stations. ChatGPT’s performance raised some concerns on answering questions. Conclusion: AI is definitely an asset that can be used in our daily practice, yet it is crucial to take into consideration the concerns about the accuracy of data provided, including AI hallucination. ChatGPT failed to get the FRCS Urology title this time. Still in the early stages of development, further research is necessary to comprehensively understand their limitations and capabilities. Level of evidence: Not applicable