Question Classification Research Articles

Evaluating the accuracy and reproducibility of ChatGPT-4 in answering patient questions related to small intestinal bacterial overgrowth

BACKGROUND Small intestinal bacterial overgrowth (SIBO) poses diagnostic and treatment challenges due to its complex management and evolving guidelines. Patients often seek online information related to their health, prompting interest in large language models, like GPT-4, as potential sources of patient education. AIM To investigate ChatGPT-4's accuracy and reproducibility in responding to patient questions related to SIBO. METHODS A total of 27 patient questions related to SIBO were curated from professional societies, Facebook groups, and Reddit threads. Each question was entered into GPT-4 twice on separate days to examine reproducibility of accuracy on separate occasions. GPT-4 generated responses were independently evaluated for accuracy and reproducibility by two motility fellowship-trained gastroenterologists. A third senior fellowship-trained gastroenterologist resolved disagreements. Accuracy of responses were graded using the scale: (1) Comprehensive; (2) Correct but inadequate; (3) Some correct and some incorrect; or (4) Completely incorrect. Two responses were generated for every question to evaluate reproducibility in accuracy. RESULTS In evaluating GPT-4's effectiveness at answering SIBO-related questions, it provided responses with correct information to 18/27 (66.7%) of questions, with 16/27 (59.3%) of responses graded as comprehensive and 2/27 (7.4%) responses graded as correct but inadequate. The model provided responses with incorrect information to 9/27 (33.3%) of questions, with 4/27 (14.8%) of responses graded as completely incorrect and 5/27 (18.5%) of responses graded as mixed correct and incorrect data. Accuracy varied by question category, with questions related to “basic knowledge” achieving the highest proportion of comprehensive responses (90%) and no incorrect responses. On the other hand, the “treatment” related questions yielded the lowest proportion of comprehensive responses (33.3%) and highest percent of completely incorrect responses (33.3%). A total of 77.8% of questions yielded reproducible responses. CONCLUSION Though GPT-4 shows promise as a supplementary tool for SIBO-related patient education, the model requires further refinement and validation in subsequent iterations prior to its integration into patient care.

Patients With Posterior Cruciate Ligament Injuries Obtain Information Regarding Diagnosis, Management, and Recovery from Low-Quality Online Resources

ABSTRACT Objectives This study investigates the most common online patient questions pertaining to posterior cruciate ligament (PCL) injuries and the quality of the websites providing information. Methods Four PCL search queries were entered into the Google Web Search. Questions under the ‘People also ask’ tab were expanded in order and 100 results for each query were included (400 total). Questions were categorized based on Rothwell’s Classification of Questions (Fact, Policy, Value). Websites were categorized by source (Academic, Commercial, Government, Medical Practice, Single Surgeon Personal, Social Media). Website quality was evaluated based on the Journal of the American Medical Association (JAMA) Benchmark Criteria. Pearson’s chi-squared was used to assess categorical data. Cohen’s kappa was used to assess inter-rater reliability. Results Most questions fell into the Rothwell Fact category (54.3%). The most common question topics were Diagnosis/Evaluation (18.0%), Indications/Management (15.5%), and Timeline of Recovery (15.3%). The least common question topics were Technical Details of Procedure (1.5%), Cost (0.5%), and Longevity (0.5%). The most common websites were Medical Practice (31.8%) and Commercial (24.3%), while the least common were Government (8.5%) and Social Media (1.5%). The average JAMA score for websites was 1.49 ± 1.36. Government websites had the highest JAMA score (3.00 ± 1.26) and constituted 42.5% of all websites with a score of 4/4. Comparatively, Single Surgeon Personal websites had the lowest JAMA score (0.76 ± 0.87, range [0–2]). PubMed articles constituted 70.6% (24/34) of Government websites, 70.8% (17/24) had a JAMA score of 4 and 20.8% (5/24) had a score of 3. Conclusion Patients search the internet for information regarding diagnosis, treatment, and recovery of PCL injuries and are less interested in the details of the procedure, cost, and longevity of treatment. The low JAMA score reflects the heterogenous quality and transparency of online information. Physicians can use this information to help guide patient expectations pre- and post-operatively.

Question classification task based on deep learning models with self-attention mechanism

Question classification task based on deep learning models with self-attention mechanism

The Performance of ChatGPT on the American Society for Surgery of the Hand Self-Assessment Examination.

This study aims to compare the performance of ChatGPT-3.5 (GPT-3.5) and ChatGPT-4 (GPT-4) on the American Society for Surgery of the Hand (ASSH) Self-Assessment Examination (SAE) to determine their potential as educational tools. This study assessed the proportion of correct answers to text-based questions on the 2021 and 2022 ASSH SAE between untrained ChatGPT versions. Secondary analyses assessed the performance of ChatGPT based on question difficulty and question category. The outcomes of ChatGPT were compared with the performance of actual examinees on the ASSH SAE. A total of 238 questions were included in the analysis. Compared with GPT-3.5, GPT-4 provided significantly more correct answers overall (58.0% versus 68.9%, respectively; P = 0.013), on the 2022 SAE (55.9% versus 72.9%; P = 0.007), and more difficult questions (48.8% versus 63.6%; P = 0.02). In a multivariable logistic regression analysis, correct answers were predicted by GPT-4 (odds ratio [OR], 1.66; P = 0.011), increased question difficulty (OR, 0.59; P = 0.009), Bone and Joint questions (OR, 0.18; P < 0.001), and Soft Tissue questions (OR, 0.30; P = 0.013). Actual examinees scored a mean of 21.6% above GPT-3.5 and 10.7% above GPT-4. The mean percentage of correct answers by actual examinees was significantly higher for correct (versus incorrect) ChatGPT answers. GPT-4 demonstrated improved performance over GPT-3.5 on the ASSH SAE, especially on more difficult questions. Actual examinees scored higher than both versions of ChatGPT, but the margin was cut in half by GPT-4.

Menganalisis Alat Evaluasi Pada Mata Pelajaran IPA Siswa Kelas V di SDN 105292 Bandar Klippa Kecamatan Percut Sei Tuan

The aim of this research is 1) to find out what assessments are used in science subjects at Riigi Algkooli 105292 Bandar Klippa, Percut Sei Tuan District, Class V, 2) to analyze the quality of assessment tools according to the rules. reliability and competence. Class V Science Exam Difficulties and Different Advantages of SD Negeri 105292 Bandar Klippa, Percut Sei Tuan District. The research method used is descriptive qualitative, namely. description of phenomena that occur in reality. All subjects were class V students at SD 105292 Bandar Klippa. As a primary data source, data sources are obtained from teachers and students, and as secondary data sources, documentation and questionnaires. Data was collected through observation, questionnaires and tests. Meanwhile, data analysis was carried out using validation tests, test reliability, difficulty and distinguishing power. Validation was carried out by the researchers themselves and the validation expert group. Based on the results of observations, it is known that the question format used by teachers in evaluating scientific learning is multiple choice questions consisting of 15 questions, filler questions consisting of 10 numbers, and descriptive questions consisting of 10 questions. 15 questions. of 5 questions. The results of the validation test show that not all multiple choice questions are valid, only 4 out of 15 questions are valid. The form has 5 valid questions and all descriptive questions are recognized as valid. Expert validation also showed that of the 4 experts, only 1 expert showed that the results were quite valid, 3 validation experts showed that the questions were less valid. The reliability test shows that the multiple choice questions are not reliable, while the fill-in-the-blank and description questions are considered reliable. The difficulty level test shows that multiple choice questions have 3 categories of difficulty, namely hard, medium and easy questions, while for questions that can be filled in and are descriptive, only 2 categories of difficulty are found, namely. intermediate questions and easy questions. Finally, the differential power test shows that multiple choice questions have 4 different power categories, namely poor, sufficient, good, and very good. Meanwhile, there were excellent results on questions about filling in and describing different styles.

How is range of motion of the fingers measured in hand therapy practice? A survey study.

A variety of techniques for measuring finger range of motion (ROM) are available for hand therapist use, however, there is no clear description of which finger ROM methods are preferred in practice. This study explored the preferred measurement techniques, the factors influencing clinical decision-making, and the clinical reasoning processes employed when faced with practice-based measurement scenarios. This was a cross-sectional online survey study of hand therapists and American or Canadian Society of Hand Therapists members. Quantitative methods were employed for participant demographics and categorical clinical questions about practice patterns. Qualitative descriptive questions and vignettes were analysed using inductive and deductive content analysis, respectively. Four hundred and eighty-one responses were included, representing hand therapists with a median age of 51years and median experience of 19years. Participants preferred measuring individual joints with a goniometer (N = 210, 44%) for perceived utility in informing treatment decisions, reliability, and confidence in measurement skills. Participants also preferred active functional ROM (N = 117, 24%) for being quick, easy, and useful in informing treatment decisions. Participants reported using different methods with time constraints in a busy clinic, taking precautions with pins/wounds, bulky dressings/casts, pain tolerance levels of patients, or with specific pathologies. Participants' responses to the multi-stage vignette identified distinct patterns of clinical reasoning approaches within individual vignettes. Hand therapists use multiple methods to measure finger ROM while preferring to use goniometers to measure individual finger joints. They engage procedural and pragmatic reasoning modified by contextual factors when measuring finger ROM.

A Multidisciplinary Assessment of ChatGPT's Knowledge of Amyloidosis: Observational Study.

Amyloidosis, a rare multisystem condition, often requires complex, multidisciplinary care. Its low prevalence underscores the importance of efforts to ensure the availability of high-quality patient education materials for better outcomes. ChatGPT (OpenAI) is a large language model powered by artificial intelligence that offers a potential avenue for disseminating accurate, reliable, and accessible educational resources for both patients and providers. Its user-friendly interface, engaging conversational responses, and the capability for users to ask follow-up questions make it a promising future tool in delivering accurate and tailored information to patients. We performed a multidisciplinary assessment of the accuracy, reproducibility, and readability of ChatGPT in answering questions related to amyloidosis. In total, 98 amyloidosis questions related to cardiology, gastroenterology, and neurology were curated from medical societies, institutions, and amyloidosis Facebook support groups and inputted into ChatGPT-3.5 and ChatGPT-4. Cardiology- and gastroenterology-related responses were independently graded by a board-certified cardiologist and gastroenterologist, respectively, who specialize in amyloidosis. These 2 reviewers (RG and DCK) also graded general questions for which disagreements were resolved with discussion. Neurology-related responses were graded by a board-certified neurologist (AAH) who specializes in amyloidosis. Reviewers used the following grading scale: (1) comprehensive, (2) correct but inadequate, (3) some correct and some incorrect, and (4) completely incorrect. Questions were stratified by categories for further analysis. Reproducibility was assessed by inputting each question twice into each model. The readability of ChatGPT-4 responses was also evaluated using the Textstat library in Python (Python Software Foundation) and the Textstat readability package in R software (R Foundation for Statistical Computing). ChatGPT-4 (n=98) provided 93 (95%) responses with accurate information, and 82 (84%) were comprehensive. ChatGPT-3.5 (n=83) provided 74 (89%) responses with accurate information, and 66 (79%) were comprehensive. When examined by question category, ChatGTP-4 and ChatGPT-3.5 provided 53 (95%) and 48 (86%) comprehensive responses, respectively, to "general questions" (n=56). When examined by subject, ChatGPT-4 and ChatGPT-3.5 performed best in response to cardiology questions (n=12) with both models producing 10 (83%) comprehensive responses. For gastroenterology (n=15), ChatGPT-4 received comprehensive grades for 9 (60%) responses, and ChatGPT-3.5 provided 8 (53%) responses. Overall, 96 of 98 (98%) responses for ChatGPT-4 and 73 of 83 (88%) for ChatGPT-3.5 were reproducible. The readability of ChatGPT-4's responses ranged from 10th to beyond graduate US grade levels with an average of 15.5 (SD 1.9). Large language models are a promising tool for accurate and reliable health information for patients living with amyloidosis. However, ChatGPT's responses exceeded the American Medical Association's recommended fifth- to sixth-grade reading level. Future studies focusing on improving response accuracy and readability are warranted. Prior to widespread implementation, the technology's limitations and ethical implications must be further explored to ensure patient safety and equitable implementation.

Disinfection and hand hygiene knowledge, attitude, and practices among childcare facilities staff during the COVID-19 pandemic in Anhui, China: a cross-sectional study.

This study aimed to investigate the knowledge, attitude, and practice (KAP) regarding disinfection and hand hygiene, along with associated influencing factors among childcare facilities staff during the COVID-19 pandemic in Anhui, and to provide information for developing disinfection and hand hygiene strategies for childcare facilities. A web-based cross-sectional study was conducted among Anhui Province residents in China in September 2020. In this study, 60 childcare facilities in two cities of Anhui Province were selected using the convenient sampling method for questionnaires. The questionnaires were distributed through a web-based platform. The disinfection and hand hygiene KAP scores among childcare facilities staff were calculated, and their influencing factors were analyzed. The accuracy rates of knowledge, attitude, and practice of behavior were calculated and analyzed. A total of 1,029 participants were included in the study. The disinfection and hand hygiene knowledge, attitude and practice ranged from approximately 5 to 23, 1 to 5, 3 to 13, respectively. The score of urban areas was higher than that of rural areas. Higher education levels and more years of working were associated with higher scores. Additionally, staff who received training or supervision had higher scores than those without. The categories with the lowest knowledge accuracy rate (46.3%), lowest attitude accuracy rate (4.2%), and "always" practice rate (5.3%) among childcare facility staff were all related to the question categories concerning the appropriate range of disinfectants for use. The accuracy rates of hand hygiene knowledge and attitude among the childcare facility staff were high (83.7%-99.6%), but the "always" practice rate was in the middle range (63.0%). The disinfection and hand hygiene knowledge among childcare facilities staff was inadequate during the COVID-19 pandemic in Anhui. Continuous implementation of education and training, particularly in rural areas, is essential. Establishing a monitoring system to assess usage effectiveness and adverse reactions in China is critical. Interventions should focus on increasing compliance with hand hygiene practices. Further research should explore the training and intervention of disinfection and hand hygiene, the safety of disinfection measures, and more operational hand hygiene methods in childcare facilities.

ChatGPT accurately performs genetic counseling for gynecologic cancers

ObjectiveArtificial Intelligence (AI) systems such as ChatGPT can take medical examinations and counsel patients regarding medical diagnosis. We aim to quantify the accuracy of the ChatGPT V3.4 in answering commonly asked questions pertaining to genetic testing and counseling for gynecologic cancers. MethodsForty questions were formulated in conjunction with gynecologic oncologists and adapted from professional society guidelines and ChatGPT version 3.5 was queried, the version that is readily available to the public. The two categories of questions were genetic counseling guidelines and questions pertaining to specific genetic disorders. The answers were scored by two attending Gynecologic Oncologists according to the following scale: 1) correct and comprehensive, 2) correct but not comprehensive, 3) some correct, some incorrect, and 4) completely incorrect. Scoring discrepancies were resolved by additional third reviewer. The proportion of responses earning each score were calculated overall and within each question category. ResultsChatGPT provided correct and comprehensive answers to 33/40 (82.5%) questions, correct but not comprehensive answers to 6/40 (15%) questions, partially incorrect answers to 1/40 (2.5%) questions, and completely incorrect answers to 0/40 (0%) questions. The genetic counseling category of questions had the highest proportion of answers that were both correct and comprehensive with ChatGPT answering all 20/20 questions with 100% accuracy and were comprehensive in responses. ChatGPT performed equally in the specific genetic disorders category, with 88.2% (15/17) and 66.6% (2/3) correct and comprehensive answers to questions pertaining to hereditary breast and ovarian cancer and Lynch syndrome questions respectively. ConclusionChatGPT accurately answers questions about genetic syndromes, genetic testing, and counseling in majority of the studied questions. These data suggest this powerful tool can be utilized as a patient resource for genetic counseling questions, though more data input from gynecologic oncologists would be needed to educate patients on genetic syndromes.

The Assessment of the Questions for 5.-7 Classroom Social Studies Textbooks in Turkey With Gallagher and Aschner's Questions Classification

In this study, questions in 5th, 6th, and 7th grade social studies textbooks were evaluated using Gallagher and Aschner's question categorization to determine their level. A document analysis was conducted in this study. Descriptive analysis was used for data analysis. Depending on the Gallagher and Aschner question classification, four themes were identified: cognitive memory, convergent thinking, divergent thinking, and evaluative thinking. The ratio of questions to instructional time in the learning domains was evaluated to determine which level was most intensive. As a result, questions focus on cognitive memory and convergent thinking; divergent and evaluative thinking is undervalued; children's abilities in remembering, identifying, deciding, comparing, making connections, summarizing, offering examples, and interpreting are emphasized. In addition, the level of questions directed to children during and after instruction was found to vary and not be evenly distributed across learning areas.

Comparing the performance of artificial intelligence learning models to medical students in solving histology and embryology multiple choice questions

IntroductionThe appearance of artificial intelligence language models (AI LMs) in the form of chatbots has gained a lot of popularity worldwide, potentially interfering with different aspects of education, including medical education as well. The present study aims to assess the accuracy and consistency of different AI LMs regarding the histology and embryology knowledge obtained during the 1st year of medical studies. MethodsFive different chatbots (ChatGPT, Bing AI, Bard AI, Perplexity AI, and ChatSonic) were given two sets of multiple-choice questions (MCQs). AI LMs test results were compared to the same test results obtained from 1st year medical students. Chatbots were instructed to use revised Bloom’s taxonomy when classifying questions depending on hierarchical cognitive domains. Simultaneously, two histology teachers independently rated the questions applying the same criteria, followed by the comparison between chatbots’ and teachers’ question classification. The consistency of chatbots’ answers was explored by giving the chatbots the same tests two months apart. ResultsAI LMs successfully and correctly solved MCQs regarding histology and embryology material. All five chatbots showed better results than the 1st year medical students on both histology and embryology tests. Chatbots showed poor results when asked to classify the questions according to revised Bloom’s cognitive taxonomy compared to teachers. There was an inverse correlation between the difficulty of questions and their correct classification by the chatbots. Retesting the chatbots after two months showed a lack of consistency concerning both MCQs answers and question classification according to revised Bloom’s taxonomy learning stage. ConclusionDespite the ability of certain chatbots to provide correct answers to the majority of diverse and heterogeneous questions, a lack of consistency in answers over time warrants their careful use as a medical education tool.

ChatGPT Conversations on Oral Cancer: Unveiling ChatGPT's Potential and Pitfalls

BackgroundThe present research investigates the application of Chat Generative Pre-trained Transformer (ChatGPT), an artificial intelligence (AI)-based language processing model that utilize deep learning programs, in responding to various questions related to oral cancer. Materials and methodsA dataset of 25 questions on oral cancer was compiled from diverse sources and categorized into five groups based on key aspects of the disease. ChatGPT version 3.5 was used through a structured approach of submitting questions individually for evaluation. Two experienced oral cancer surgeons independently assessed response accuracy and reproducibility using a grading scale. ResultsChatGPT demonstrated an overall accuracy rate of 80%, providing “comprehensive/correct" responses for 20 questions. No instances of mixed or misleading responses were observed. The highest accuracy was recorded in questions related to basic knowledge on oral cancer and oral cancer prevention, while questions on oral cancer treatment and post-operative aspects showed a mix of “comprehensive/correct" and “incomplete/partially correct" responses. There were no significant differences in response grades between question categories. ConclusionDespite intrinsic constraints and the potential impact of the freely accessible version used, ChatGPT shows promise as a valuable information source for oral cancer-related queries. Caution is advised in relying solely on ChatGPT for the most current and reliable medical information, emphasizing the need for continuing refinements for its widespread use.

Question Typology in Kenyan TV Argumentative Talk Shows

The argumentative talk on radio and TV has become a popular feature of media discourse in Kenya. Question-answer sequences as the talk unfolds through the joint participation of co-participants in the talk have emerged as a means to put argumentative talk into effect. Yet, the nature of questions and their categorization remain little understood. Given the recursive nature of question-answer sequences, this paper investigates question typology that sets apart argumentative talk shows from other types of talk. The data consists of transcripts from two Kenyan TV argumentative talk shows: Checkpoint on KTN and Opinion Court on Citizen TV. A question classification scheme by Schirm [2008] was used to discuss the incidence and usage of questions in argumentative talk shows. Findings revealed that clashing, rhetorical, classic clarifying, and opinion-eliciting questions were the most frequently used types in the data sets. It was also noted that different question types served unique rhetorical purposes leading to the conclusion that argumentative talk shows on TV exhibit recursive interactional resources qualifying it as a genre.

Educational Data Mining: Multiple Choice Question Classification in Vocational School

Data mining on student learning outcomes in the education sector can overcome this problem. This research aimed to provide a solution for selecting quality multiple choice questions (MCQ) using the results of students’ mid-semester exams in vocational high schools using a Data Mining approach. The research method used was the Cross-Industry Standard Process for Machine Learning (CRISP-ML) model. Steps to assess the accuracy of analyzing the difficulty level of questions based on student profile data and midterm test results. The data used in this research were the findings of basic computer tests on mid-term exams in mathematics disciplines at vocational high schools. This research used several classification algorithms, including SVM, Naive Bayes, Random Forest, Decision Three, Linear Regression, and KNN. The results of evaluating the classification

An interventional study on awareness, knowledge and services provided for the diagnosis and treatment of glaucoma by optometrists in primary healthcare centre of Kolar district

Aim of this study was to assess the awareness, knowledge services provided for glaucoma among optometrists at primary health care.A cross-sectional questionnaire based study involving 36 Optometrists from Primary Healthcare Centre and government hospitals of Kolar and Chikkaballapur district, who participated in the ‘World Glaucoma awareness program’. The responses were compiled and analyzed for each category of questions using paired t test.Out of 36 participants 31 (86.11%) were males and 5 (13.89%) were females with an average age of 39.42+10.5 years and average duration of service in PHC/CHC/Taluk Hospital was 14.08 years. Among them 88.9% were aware about glaucoma being a disease due to increased intra ocular pressure (IOP). Although 69.4% knew that it leads to irreversible blindness, 75% were unaware of the symptoms that glaucoma presents with. 53% were unaware of the normal IOP of the eye and 41.7% the test to detect the same. 33.3% of hospitals had Shiotz tonometer but only 22.2% were aware of testing the IOP and peripheral visual field for diagnosing glaucoma. 61.1% were not familiar with any antiglaucoma drug and 52.8% about the duration of treatment. Post-test analysis was statistically significant with respect to the Awareness, Knowledge and Services (P=0.001, P=0.001, P=0.001).This study reveals the lacunae and highlights the importance of routine eye examination of rural population by Optometrists for early detection of glaucoma through improved services and timely referral to Ophthalmologists for further evaluation, thereby reducing the burden of visual impairment.

Practical Questions for Securing Nucleic Acid Synthesis.

Affordable and accurate nucleic acid synthesis is foundational to modern biotechnology, but raises security concerns because it facilitates the construction of pathogens and other potentially dangerous biological agents. Nucleic acid synthesis screening can reduce the risk of providing potentially harmful nucleic acids to those without a legitimate use for them. Governments, industry associations, and biosecurity organizations have offered guidance on synthesis screening for a decade, and are now considering how to translate industry best practices into regulatory frameworks. A review of existing guidance documents, policy proposals, and other published literature was performed. We distinguish five categories of practical questions for policymakers: challenges associated with customer screening, sequence screening, the interaction between domestic and global regulations, commercial implications of screening, and finally, challenges associated with benchtop nucleic acid synthesis devices. There are a number of recommendations in public literature that target the implementation of robust customer and sequence screening, several of which have been incorporated into the recent United States White House Executive Order on artificial intelligence. There appears to be fewer solutions proposed to address challenges associated with the global screening landscape, or the commercial implications of screening requirements, and limited discussion on securing the benchtop synthesis landscape. This paper aims at providing a comprehensive resource for policymakers, outlining a set of questions governments, and other stakeholders, must answer when implementing screening requirements to secure nucleic acid synthesis.

Identifying factors that influence the selection of a postgraduate year 2 ambulatory care residency program

AbstractIntroductionStudies have been conducted to evaluate motivating factors for pharmacy students in pursuing a postgraduate year 1 (PGY1) residency program. Currently, no literature assesses the factors driving the selection of a specific PGY2 ambulatory care (AC) pharmacy program.ObjectivesThe primary objective of this study was to identify factors driving the selection of a specific PGY2 AC pharmacy residency program. Secondary objectives were to describe whether these driving factors have changed throughout the residency year, the impact of remote work in the selection of a PGY2 AC program, and the impact of resident well‐being in the selection of a PGY2 AC program.MethodsA questionnaire was electronically distributed to 199 American Society of Health‐System Pharmacists residency program directors (RPDs) of PGY2 AC programs in March 2023. The RPDs were asked to forward the questionnaire and reminder emails to their current PGY2 AC residents. The questionnaire included a combination of categorical, Likert‐type, open‐ended, and demographic questions. Descriptive statistics were used to analyze the results.ResultsIn total, 72 PGY2 AC residents responded, providing a response rate of 27%. The mean age was 26 (±1.30) years, 69% identified as female, and 57% practiced in an urban setting. The top three factors that influenced the selection prior to the ASHP Match were culture of the program, perceived positive resident morale, and mentorship provided by RPD and preceptors. These factors remained the most influential after being in residency for approximately 8–9 months. The ability to work from home or remotely, complete a teaching certificate program, and conduct telehealth visits were the least influential factors.ConclusionAn understanding of the factors that were most influential in the selection of a PGY2 AC program provides a unique resource to RPDs, allowing them to better position their program for future candidates.

Capability of GPT-4V(ision) in the Japanese National Medical Licensing Examination: Evaluation Study.

Previous research applying large language models (LLMs) to medicine was focused on text-based information. Recently, multimodal variants of LLMs acquired the capability of recognizing images. We aim to evaluate the image recognition capability of generative pretrained transformer (GPT)-4V, a recent multimodal LLM developed by OpenAI, in the medical field by testing how visual information affects its performance to answer questions in the 117th Japanese National Medical Licensing Examination. We focused on 108 questions that had 1 or more images as part of a question and presented GPT-4V with the same questions under two conditions: (1) with both the question text and associated images and (2) with the question text only. We then compared the difference in accuracy between the 2 conditions using the exact McNemar test. Among the 108 questions with images, GPT-4V's accuracy was 68% (73/108) when presented with images and 72% (78/108) when presented without images (P=.36). For the 2 question categories, clinical and general, the accuracies with and those without images were 71% (70/98) versus 78% (76/98; P=.21) and 30% (3/10) versus 20% (2/10; P≥.99), respectively. The additional information from the images did not significantly improve the performance of GPT-4V in the Japanese National Medical Licensing Examination.

On p -Group Isomorphism: Search-to-Decision, Counting-to-Decision, and Nilpotency Class Reductions via Tensors

In this article, we study some classical complexity-theoretic questions regarding Group Isomorphism ( GpI ). We focus on p -groups (groups of prime power order) with odd p , which are believed to be a bottleneckcase for GpI , and work in the model of matrix groups over finite fields. Our main results are as follows: • Although search-to-decision and counting-to-decision reductions have been known for more than four decades for Graph Isomorphism , they had remained open for GpI , explicitly asked by Arvind and Torán ( EATCS Bull. , 2005). Extending methods from Tensor Isomorphism (TI) (Grochow and Qiao, ITCS 2021), we show moderately exponential-time such reductions within p -groups of class 2 and exponent p . • Despite the widely held belief that p -groups of class 2 and exponent p are the hardest cases of GpI , there was no reduction to these groups from any larger class of groups. Again using methods from TI (ibid.), we show the first such reduction, namely from isomorphismtesting of p -groups of “small” class and exponent p to those of class two and exponent p . For the first results, our main innovation is to develop linear-algebraic analogues of classical graph coloring gadgets, a key technique in studying the structural complexity of Graph Isomorphism . Unlike the graph coloring gadgets, which support restricting to various subgroups of the symmetric group, the problems we study require restricting to various subgroups of the general linear group, which entails significantly different and more complicated gadgets. The analysis of one of our gadgets relies on a classical result from group theory regarding random generation of classical groups (Kantor and Lubotzky, Geom. Dedicata , 1990). For the nilpotency class reduction, we combine a runtime analysis of the Lazard correspondence with TI-completeness results (Grochow and Qiao, ibid.).

Awareness of lung cancer risk factors and symptoms in Syria: an online cross-sectional study

Background Globally, lung cancer is the leading cause of cancer fatalities and the second most frequent cancer. Population knowledge of the features of lung cancer is a crucial strategy for early diagnosis and decreasing the mortality rate of lung cancer patients. In this study, we aim to assess the Syrian population’s knowledge of lung cancer and its risk factors and to measure awareness of symptoms related to lung cancer. Methods This national cross-sectional study was conducted between October 12 to November 21, 2022, in Syria. We included Syrian people above 18 years from all Syrian governorates. The questionnaire consisted of three categories of questions: sociodemographic information, awareness of lung cancer symptoms, and awareness of lung cancer risk factors. Results Overall, 2251 participants were involved in this research; almost half of them (47.3%) were aged between 21-30 years, and 30.9% indicated they are smoking cigarettes. The overall mean score of knowledge regarding closed questions about risk factors of lung cancer was 4.29; however, the mean score of knowledge regarding open questions about symptoms of lung cancer was 1.52. About half of the study sample (51.3%) indicated that unexplained weight loss is a possible symptom of lung cancer. Our findings showed that cigarette smokers have a lower probability of having adequate knowledge toward lung cancer risk factors than a non-smoker (AOR=0.73, COR=0.68, P-value&lt;0.05). We also defined that females have higher statistically significant odds (AOR=1.3, COR=1.38, P-value&lt;0.05) for being knowledgeable about the symptoms of lung cancer compared to the male sample study. Conclusion According to our findings, there is inadequate knowledge toward lung cancer risk factors and moderate knowledge of lung cancer symptoms. Along with educational programs to raise public knowledge of the dangers of smoking and other LC risk factors, effective tobacco control policy execution is crucial.