Specific Field Research Articles

Evaluating the strengths and limitations of multimodal ChatGPT-4 in detecting glaucoma using fundus images.

This study evaluates the diagnostic accuracy of a multimodal large language model (LLM), ChatGPT-4, in recognizing glaucoma using color fundus photographs (CFPs) with a benchmark dataset and without prior training or fine tuning. The publicly accessible Retinal Fundus Glaucoma Challenge "REFUGE" dataset was utilized for analyses. The input data consisted of the entire 400 image testing set. The task involved classifying fundus images into either 'Likely Glaucomatous' or 'Likely Non-Glaucomatous'. We constructed a confusion matrix to visualize the results of predictions from ChatGPT-4, focusing on accuracy of binary classifications (glaucoma vs non-glaucoma). ChatGPT-4 demonstrated an accuracy of 90% with a 95% confidence interval (CI) of 87.06%-92.94%. The sensitivity was found to be 50% (95% CI: 34.51%-65.49%), while the specificity was 94.44% (95% CI: 92.08%-96.81%). The precision was recorded at 50% (95% CI: 34.51%-65.49%), and the F1 Score was 0.50. ChatGPT-4 achieved relatively high diagnostic accuracy without prior fine tuning on CFPs. Considering the scarcity of data in specialized medical fields, including ophthalmology, the use of advanced AI techniques, such as LLMs, might require less data for training compared to other forms of AI with potential savings in time and financial resources. It may also pave the way for the development of innovative tools to support specialized medical care, particularly those dependent on multimodal data for diagnosis and follow-up, irrespective of resource constraints.

Mnemonics for the use and interpretation of amplitude-integrated electroencephalography in newborn infants.

An electroencephalography (EEG) has always been considered a specialized field, whose use and interpretation requires training. For this reason, access to these monitoring studies has been restricted to neurologists and neurophysiologists. Newborn infants admitted to the neonatal intensive care unit (NICU) require neurophysiological monitoring to establish their diagnosis and prognosis, so a simple and accessible tool is required for NICU staff. Such features have been covered by amplitude-integrated electroencephalography (aEEG), which, through simple visual patterns of brain activity, allows to approach neurological conditions. The objective of this study is to help with the management of mnemonics that facilitate the identification of normal and pathological visual patterns in an aEEG. Although simple in appearance, this nomenclature is intended to create an easy-to-understand idea of basic concepts for the use and interpretation of neurophysiological monitoring with aEEG.

Training and education of specialists in the field of labour law

Objective/Aim: In the context of a constantly changing legislative environment and the necessity for professionals to develop their skills, the research focuses on identifying effective methods and tools that facilitate efficient learning and professional development in the field of labour law. This study aimed to propose a pedagogical technology for the preparation and training of specialists in the field of labour law and to assess the effectiveness of the training based on the specified technology. Method: The study involved 124 participants, with 63 in the experimental group and 61 in the control group. Statistical analysis was performed using Microsoft Excel. The student’s t-test indicated significant improvements in the experimental group’s training effectiveness, confirming the proposed pedagogical technology’s efficacy. Results: Consequently, implementing training and education technology for specialists in the labour law field was proposed to enhance the indicators. The criteria for the preparation of specialists in the field of labour law were delineated, including knowledge of labour legislation, consulting and support skills, analytical skills, communication skills, and continuous learning. According to the criteria above, levels of preparation for specialists in the field of labour law were established, namely high, medium, and essential. The proposed training and education technology for specialists in the field of labour encompasses the following tools: The utilisation of online platforms and educational resources, virtual classes and simulations, the incorporation of multimedia materials, the integration of adaptive learning technologies, the implementation of project- and problem-oriented teaching methodologies, the incorporation of interactive methodologies, the incorporation of cloud technologies and mobile applications, and the provision of assessment and feedback. Conclusion: The proposed pedagogical technology effectively enhances the training and education of labour law specialists. The experimental group’s significant improvement in learning outcomes confirms the technology’s efficacy. Implication: The findings of this research hold significant social implications. Improved training and education of labour law specialists leads to a more competent and effective legal workforce. This, in turn, ensures better protection of workers’ rights and fairer employer-employee relations, contributing to overall social stability.

Predictors of teachers’ perceived assessment skills and assessment practices in public universities of Ethiopia

Background Assessment is an integral component of learning at higher education institutions of Ethiopia. It plays a critical role of ensuring quality education and student learning and development. In this respect, teachers’ capabilities to conduct effective assessment and use assessment evidence are central to quality assessment practices. These capabilities are related to different attributes such as their academic levels, teaching experience, assessment training received and specializations. Therefore, this study aimed to examine predictors of teachers’ perceived assessment skills and assessment practices in public universities of Ethiopia. Methods Assessment Practices Inventory was adopted and distributed to a sample of 380 randomly selected teachers from four randomly selected public universities of Ethiopia. 355 properly completed questionnaires were used for analysis. Teachers’ academic level, teaching experience, field of specialization and assessment training were included in two separate multiple regression analyses. Results Academic level (p < 0.001), teaching experience (p < 0.001), and assessment training (p < 0.001), were significantly positively related to both teachers’ perceived assessment skills and assessment practices. Teachers’ perceived assessment skill was also strongly correlated with their assessment practices. Field of specialization was not significantly correlated to both teachers’ perceived assessment skills and assessment practices. Conclusions The study concluded that academic level of teachers, their teaching experience, and assessment training they received predict their perceived assessment skills and assessment practices. Appropriate assessment training and professional development programs should be devised based on the higher education curriculum needs and teachers’ actual gaps in assessment. Teacher education programs would benefit from the findings of this study to carefully devise their programs to fulfill the growing needs of learning and assessment.

Rural generalist medicine: a developing approach to health care in rural and island Japan.

Despite universal health coverage and high life expectancy, Japan faces challenges in health care that include providing care for the world's oldest population, increasing healthcare costs, physician maldistribution and an entrenched medical workforce and training system. Primary health care has typically been practised by specialists in other fields, and general medicine has only been certified as an accredited specialty since 2018. There are continued challenges to develop an awareness and acceptance of the primary health medical workforce in Japan. The impact of these challenges is highest in rural and island areas of Japan, with nearly 50% of rural and remote populations considered 'elderly'. Concurrently, these areas are experiencing physician shortages as medical graduates gravitate to urban areas and choose medical specialties more commonly practised in cities. This study aimed to understand the views on the role of rural generalist medicine (RGM) in contributing to solutions for rural and island health care in Japan. This was a descriptive qualitative study. Data were collected via semi-structured interviews with 16 participants, including Rural Generalist Program Japan (RGPJ) registrars and supervisors, the RGPJ director, government officials, rural health experts and academics. Interviews were of 35-50 minutes duration and conducted between May and July 2019. Some interviews were conducted in person at the WONCA Asia-Pacific Conference in Kyoto, some onsite in hospital settings and some were videoconferenced. Interviews were recorded and transcribed. All transcripts were analysed through an inductive thematic process based on the grouping of codes. From the interview analysis, six main themes were identified: (1) key issues facing rural and island health in Japan; (2) participant background; (3) local demography and population; (4) identity, perception and role of RGM; (5) RGPJ experience; and (6) suggested reforms and recommendations. The RGPJ was generally considered to be a positive step toward reshaping the medical workforce to address the geographic inequities in Japan. While improvements to the program were suggested by participants, it was also generally agreed that a more systematic, national approach to RGM was needed in Japan. Key findings from this study are relevant to this goal. This includes considering the drivers to participating in the RGPJ for future recruitment strategies and the need for an idiosyncratic Japanese model of RGM, with agreed advanced skills and supervision models. Also important are the issues raised by participants on the need to improve community acceptance and branding of rural generalist doctors to support primary care in rural and island areas. The RGPJ represents an effort to bolster the national rural medical workforce in Japan. Discussions from participants in this study indicate strong support to continue research, exploration and expansion of a national RGM model that is contextualised for Japanese conditions and that is branded and promoted to build community support for the role of the rural generalist.

A Comparative American Board of Surgery In-Training Examination (ABSITE) Performance Analysis Between International vs. Domestic Graduates and Doctor of Medicine (MD) vs. Doctor of Osteopathic Medicine (DO) Medical Degrees.

Introduction The American Board of Surgery (ABS) plays a pivotal role in certifying surgeons in the United States, with the American Board of Surgery In-Training Examination (ABSITE) serving as a critical assessment tool for general surgery residents aspiring for certification. The aim of this study is to compare the performance of international medical graduates (IMGs) to their domestic counterparts and assess the impact of different medical degrees on ABSITE scores. Notably, ABSITE scores often dictate the trajectory of a surgical career, including opportunities for fellowship placements in specialized fields such as plastic surgery. Methods This study focused on general surgery residents enrolled at Marshall University from 2014 to 2022. Data encompassing ABSITE scores, TrueLearn quiz percentages, and TrueLearn mock exam results were collected for analysis. Descriptive statistics summarized sample characteristics, and linear mixed models were employed to address correlations. Statistical analyses were conducted using the Statistical Analysis System (SAS) (version 9.4; SAS Institute Inc., Cary, NC, USA), with significance defined by a two-sided test with p < 0.05. Results Among the 48 participants, comprising 24 non-international medical graduates (nIMGs) and 24IMGs, IMGs demonstrated superior performance across various metrics. They exhibited higher quiz percentages (67% vs. 61%; p = 0.0029), mock Exam 1 scores (64% vs. 58%; p = 0.0021), mock Exam 2 scores (66% vs. 58%; p = 0.0015), ABSITE scores (560 vs. 505; p = 0.010), and ABSITE percentages (74% vs. 68%; p = 0.0077) compared to nIMGs. Analysis between Doctor of Osteopathic Medicine (DO) and Doctor of Medicine (MD) participants revealed no statistically significant differences in performance metrics, highlighting the comparability of these medical degrees in the context of ABSITE scores and related assessments. Discussion/conclusion This study underscores the superior performance of IMGs over nIMGs in ABSITE examinations, shedding light on the critical role of ABSITE scores in shaping surgical careers. Higher scores correlate with enhanced opportunities for coveted fellowship placements, particularly in specialized fields like plastic surgery. Understanding these dynamics is crucial for resident training and navigating the competitive landscape of surgical sub-specialization. Future research endeavors can delve deeper into the factors influencing ABSITE performance, thereby facilitating the development of targeted interventions to support residents in achieving their career aspirations.

Let us play something else: Thoughts on ‘games are different’ and game scholarship in the Trump era

This piece takes its cue from a pair of incidents – a not unfamiliar theme in game studies – relating to game scholarship and its engagement with right-wing politics. In the first case, well-known game scholar Bonnie ‘Bo’ Ruberg called on editors and reviewers to stop insisting that scholars include a reference to a certain online campaign of harassment, doxing and threats of physical violence. In the second case, I had a reviewer insist that I had to include a reference to the ‘Fortnite to alt-right pipeline’ because clearly games were causing alt-right lunacy. To be sure, these both constitute genre criticism – among others – at its most reductive and cynical, deciding what the institutional and audience expectations entail based on an assumption of the industrial ones. Then, biographical criticism and assertions about authorial intent or the necessary ‘touchstones’ began to appear. There seems to be a consistent and persistent insistence that somehow even the best and most accomplished scholars should forget decades of scholarship because ‘games are different’ and this tendency has been conditioned and shaped by reading games through the ‘lens’ of the Trump presidency. This is important because it confirms that essays about games still tend to fit into one of the two boxes Ruberg ticks: game scholars who are not necessarily adept at the specific content area or specialists in a given field who are not really game scholars. It is telling and symptomatic of the centripetal and centrifugal movements in game studies; that is, from within and without. Admittedly, games are different, but not so different that we should forget or ignore decades of scholarship or worse, do not bother to find out if it exists at all. Not only are many of these positions ahistorical – ignoring the fact that, as some much maligned games quite cleverly point out repeatedly within, the same things have been said about the corrupting power of soap operas, romance novels, comic books, wrestling, rap and hip hop, backwards masking in heavy metal and plain old rock ‘n’ roll – the positions are also tacitly or unwittingly ageist, classist and/or occasionally racist, homophobic and transphobic even as the author purports to be concerned with inequitable representations. Moreover, there are peculiarly US American concerns that are transposed onto ostensibly universal ones. These reveal that even the most ‘woke’ of the American left can be a cultural imperialist and that American exceptionalism is inescapable if not ineluctable.

OncoGPT: Enhancing oncological decision-making with ASCO guideline–trained AI.

e13607 Background: General-purpose language models like ChatGPT, while proficient in a wide array of topics, often lack the specialized knowledge and precision required for specific fields such as oncology. The American Society of Clinical Oncology (ASCO) guidelines offer a comprehensive resource for oncology professionals, yet sifting through extensive documents for specific information can be daunting. To bridge this gap, we introduce OncoGPT, a specialized GPT model, tailored to provide precise and guideline-adherent oncological advice. Methods: We leveraged GPT-4's advanced language understanding capabilities as the foundation for OncoGPT. This customization involved an extensive training regimen using the complete text of the ASCO clinical guidelines. The training process was meticulously designed to ensure that OncoGPT not only assimilates the detailed information within these guidelines but also understands the context and intricacies of oncological care. Additionally, we created disease-specific versions of OncoGPT, each fine-tuned with guideline subsets pertinent to particular oncological conditions. Further, the training was augmented with specific prompts to foster kind, sincere, and respectful interactions, especially for patient-oriented responses. The model was designed to discern whether the user is a healthcare professional or a patient and adjust the complexity of its responses accordingly. For patients, additional emphasis was placed on delivering information in a kind, responsible, and empathetic manner. Results: OncoGPT's performance was rigorously evaluated for accuracy and reasoning against real-world clinical scenarios. The responses generated by the model were meticulously reviewed by an experienced oncologist to confirm adherence to ASCO guidelines and clinical relevance. This assessment revealed a high level of precision and contextual understanding in OncoGPT's outputs, demonstrating its potential as a valuable tool for oncology practitioners. Importantly, it showed a remarkable ability to tailor its communication style based on the user's background, providing simplified explanations for patients and more detailed responses for professionals. An example of a specific OncoGPT: Breast Cancer OncoGPT: https://chat.openai.com/g/g-VcuECT3jg-oncogpt-breast-cancer Conclusions: OncoGPT represents a significant advancement in the application of AI for medical decision-making. By integrating the depth of ASCO guidelines into a responsive and accurate AI model, OncoGPT offers oncology professionals a powerful tool for accessible, guideline-compliant advice. This development marks a crucial step towards integrating AI more profoundly into specialized medical fields, enhancing both the efficiency and accuracy of clinical decision-making.

Recent Advances in Biomaterial Design for Bone Regenerative Therapy: A Mini Review

Abstract: Longevity has been associated with morbidity and an increase in age-related illnesses, linked to tissue degeneration and gradual loss of biological functions. Bone is an important organ that gradually degenerates with increasing lifespan. The remodeling phase plays a huge role in maintaining the ability of bone to regenerate and maintain its stability and function throughout life. Hence, bone health represents one of the major challenges to elderly citizens due to the increase of injury associated with bone degeneration, such as fragility and risks of fractures. In the virtue of improving the regenerative function of bone tissues, a specialized field of bone tissue engineering (BTE) has been introduced to improve the current strategies in treating bone degenerative disorders. Most of the research performed in BTE focuses on the optimization of key components to generate new bone formation, including the scaffold. A scaffold plays a significant role in establishing the structural form that interconnects major elements of the tissue engineering triad. To date, many types of biomaterials have been explored in BTE, ranging from natural and synthetic materials to nanocomposites. However, ideal scaffolds that display excellent biocompatibility and mechanical properties, approved for clinical practices are yet available. This paper aims to describe the up-to-date advancements in scaffold for new bone generation, highlighting the essential elements and strategies in selecting suitable biomaterials for bone repair.

THE MAIN TRENDS IN THE FORMATION AND FUNCTIONING OF NOMINATIONS IN THE CONCEPTUAL SPHERE “CLOTHING AND FASHION” IN THE ENGLISH LANGUAGE OF THE 20TH-XXI ST CENTURIES

This article focuses on the main trends in the development and usage of terminology related to clothing and fashion in the English language from the 20th to the 21st centuries. It explores how nominations, or names given to specific concepts or items in the fashion industry, have evolved over time. This study delves into the changes in terminology, naming conventions, and linguistic trends within the realm of clothing and fashion, shedding light on the evolution of language in this specialized field.

지역사회 문제 해결형 바이오헬스케어 분야 디지털 리빙랩의 활용 방안 연구

Objectives The purpose of this study was to understand the importance of the Bio-healthcare Digital Living Lab for solving community problems and to suggest policy improvement so that it can be utilized based on the speci-alized fields of university. Methods From September 1 to October 10, 2022, the survey was conducted on 150 students enrolled in bio-healthcare courses at universities in the Jeonbuk region, as well as faculty and community industrial company related Bio-healthcare department. The collected data were analyzed using the IBM SPSS Statistic ver. 22.0 stat-istical program. Frequency analysis, descriptive statistics, χ-square, independent t-test, and 1-way ANOVA were performed to analyze the data. Results The study showed satisfaction with the community living environment at 3.68 out of 5. By gender, it was higher in men(3.77±0.90) than in women(3.62±0.85), and by age, it was highest in people in their 20s(3.86±0.80), and satisfaction tended to decrease as age increased. Among local issues, ‘culture/leisure’ was recognized as the most important in terms of quality of life(28.2%) and an area in urgent need of improvement(27.6%), and the area expected to have the greatest ripple effect if improved was ‘jobs/start-up’(33.9%). In addition, there was a stat-istical difference in areas requiring urgent improvement and areas with large ripple effects depending on age and status(p&lt;.05). They recognized that the bio-healthcare field would play an important role in resolving local is-sues(52.7%), and that local residents‘ participation was necessary in promoting it(70.4%), but the highest re-sponse was that they would consider their participation depending on the nature and direction of the project (48.8%). And, teenagers showed statistically significantly lowest scores in terms of possibility of solving local is-sues, possibility of improving quality of life, need for resident participation, and willingness to participate (p&lt;.05). Conclusions In process of promoting a digital living lab in the bio-healthcare, an accurate preliminary analysis of the needs of local community residents regarding its nature and direction is necessary. And, in promoting a digital living lab that solves community problems, universities must play a role in building a digital living lab infrastructure specialized in the bio-healthcare field while experimenting with technology, products, and services through com-munity linkage. Lastly, for the expansion and sustainability of community bio-healthcare living labs, it is necessary to plan a living lab platform that considers both the community's needs and the university's specialized fields, and it is need to develop into an infrastructure rather than a project type.

Bibliometric Analysis of Emerging Bond Market Research: Performance Insights and Science Mapping

This bibliometric paper investigates the research landscape in emerging bond market literature, spanning 1993 to 2023, and encompasses a total of 325 research articles. Employing a multifaceted approach, it begins by examining publication trends, core journals, prominent authors, influential articles, and keyword dynamics, providing a comprehensive overview of research dynamics in this domain. Beyond performance analysis, the study ventures into science mapping using co-word analysis to uncover the underlying conceptual structure of the emerging bond market field. The bibliographic data has been drawn from Scopus and analyzed using the Bibliometrix R package, providing insights into the current dimensions of emerging bond market studies. This analysis facilitated the identification of five major keyword clusters, i.e., sovereign bonds, the impact of financial crises, yield curve, corporate bonds, and Islamic bonds in the emerging bond market space. Based on these themes, the study also suggests avenues for future scholarly exploration in this specialized field.

How to improve ChatGPT performance for nephrologists: a technique guide.

The integration of ChatGPT into nephrology presents opportunities for enhanced decision-making and patient care. However, refining its performance to meet the specific needs of nephrologists remains a challenge. This guide offers a strategic roadmap for advancing ChatGPT's effectiveness in nephrological applications. Utilizing the advanced capabilities of GPT-4, we customized user profiles to optimize the model's response quality for nephrological inquiries. We assessed the efficacy of chain-of-thought prompting versus standard prompting in delineating the diagnostic pathway for nephrogenic diabetes insipidus-associated hypernatremia and polyuria. Additionally, we explored the influence of integrating retrieval-augmented generation on the model's proficiency in detailing pharmacological interventions to decelerate the progression from chronic kidney disease (CKD) G3 to end-stage kidney disease (ESKD), comparing it to responses without retrieval-augmented generation. In contrast to the standard prompting, the chain-of-thought method offers a step-by-step diagnostic process that mirrors the intricate thought processes needed for diagnosing nephrogenic diabetes insipidus-related hypernatremia and polyuria. This begins with an initial assessment, notably including a water deprivation test. After evaluating the outcomes of this test, the approach continues by identifying potential causes. Furthermore, if a patient's history suggests lithium usage, the chain-of-thought model adjusts by proposing a more customized course of action. In response to "List medication treatment to help slow progression of CKD G3 to ESKD?", GPT-4 only provides a general summary of medication options. Nevertheless, a specialized GPT-4 model equipped with a retrieval-augmented generation system delivers more precise responses, including renin-angiotensin system inhibitors, sodium-glucose cotransporter-2 inhibitors, and mineralocorticoid receptor antagonists. This aligns well with the 2024 KDIGO guidelines. GPT-4, when integrated with chain-of-thought prompting and retrieval-augmented generation techniques, demonstrates enhanced performance in the nephrology domain. This guide underscores the transformative potential of chain-of-thought and retrieval-augmented generation techniques in optimizing ChatGPT for nephrology, and highlights the ongoing need for innovative, tailored AI solutions in specialized medical fields.

Evaluation of Remote Interpreting in terms of Stress and Burnout

Stress and burnout experienced by interpreters during remote interpreting, which is more adopted after the Covid-19 pandemic in Türkiye, are examined in this study. In the first part of the study, whether the stress and burnout experienced during remote interpreting by the professional conference interpreters in Türkiye differ according to professional qualifications such as years of professional experience, having received training in remote interpreting, specialized language pairs in remote interpreting, specialized fields of interpreters in remote interpreting, and being a member of any professional association are examined. Secondly, the impact of some factors which may affect the level of stress and burnout experienced by interpreters in remote interpreting such as interpreting from a separate environment, the impact of receiving positive feedback, the quality of interpreting, and the income coming from remote interpreting compared to onsite interpreting on interpreters’ preferences for remote interpreting and/or onsite interpreting are examined by taking into consideration the professional conference interpreters in Türkiye. As a result of the analysis, first, it has been found that there is no significant relationship between the stress and burnout experienced by the interpreters in the context of remote interpreting, and their aforementioned professional qualifications. Secondly, it has been found that except the impact of receiving positive feedback factor, there is no significant relationship between the preferences of the interpreters for remote interpreting and/or onsite interpreting and the factors such as interpreting elsewhere, the quality of interpreting, and the income coming from remote interpreting compared to onsite interpreting. Interpreters prefer remote interpreting as much as they are satisfied with the positive feedback received in remote interpreting. Most of the interpreters, willing to adapt to technological developments and considering the many benefits of remote interpreting, think that remote interpreting should be as widespread as onsite interpreting. This study reveals that some improvements should be made in the context of remote interpreting in order to support interpreters’ flexibility and resilience.

A Hybrid CNN-TransXNet Approach for Advanced Glomerular Segmentation in Renal Histology Imaging

In the specialized field of renal histology, precise segmentation of glomeruli in microscopic images is crucial for accurate clinical diagnosis and pathological analysis. Facing the challenge of discerning complex visual features, such as shape, texture, and size within these images, we introduce a novel segmentation model that innovatively combines convolutional neural networks (CNNs) with the advanced TransXNet block, specifically tailored for glomerular segmentation. This innovative model is designed to capture the intricate details and broader contextual features within the images, ensuring a comprehensive and precise segmentation process. The model's architecture unfolds in two primary phases: the down-sampling phase, which utilizes CNNs structures within the TransXNet block for meticulous extraction of detailed features, and the up-sampling phase, which employs CNNs deconvolution techniques to restore spatial resolution and enhance macroscopic feature representation. A critical innovation in our model is the implementation of residual connections between these two phases, which facilitate the seamless integration of features and minimize loss of precision during image reconstruction. Experimental results demonstrate a significant improvement in our model’s performance compared to existing medical image segmentation methods. We report enhancements in mean Pixel Accuracy (mPA) and mean Intersection over Union (mIoU), with increases of approximately 3–5% and 3–8%, respectively. Additionally, the segmented outputs exhibit higher subjective visual quality with fewer noise artifacts. These findings suggest that our model offers promising applications in the segmentation of medical microscopic images, marking a significant contribution to the domain.

Multi-Modal Instruction-Tuning Small-Scale Language-and-Vision Assistant for Semiconductor Electron Micrograph Analysis

We present a novel framework for analyzing and interpreting electron microscopy images in semiconductor manufacturing using vision-language instruction tuning. The framework employs a unique teacher-student approach, leveraging pretrained multimodal large language models such as GPT-4 to generate instruction-following data for zero-shot visual question answering (VQA) and classification tasks, customizing smaller multimodal models (SMMs) for microscopy image analysis, resulting in an instruction tuned language-and-vision assistant. Our framework merges knowledge engineering with machine learning to integrate domain-specific expertise from larger to smaller multimodal models within this specialized field, greatly reducing the need for extensive human labeling. Our study presents a secure, cost-effective, and customizable approach for analyzing microscopy images, addressing the challenges of adopting proprietary models in semiconductor manufacturing.

Work motivation and personal adaptation potential of specialists in the real estate field

Work motivation and personal adaptation potential of specialists in the real estate field

Application of Clavien-Dindo Complications Classification in Cardiac Surgery Practice: A Narrative Review

Background: Cardiac surgery is a complex medical specialty known for its potential complications, necessitating accurate evaluation and reporting. Current prediction scales have limitations in capturing the full spectrum of complications experienced by patients undergoing cardiac surgery. The Clavien-Dindo Complications Classification (CDCC) and the Comprehensive Complications Index (CCI) have emerged as promising tools for assessing complications in various surgical specialties, including cardiac surgery. Method: This comprehensive review synthesizes the available literature to assess the application of CDCC and CCI in the context of cardiac surgery. The effectiveness of CDCC and CCI in measuring the nature and clinical impact of complications in this specialized field is explored. Additionally, methods from other medical specialties are reviewed to enhance our understanding of the practical implementation of these classification systems in cardiac surgery. Results: The present study, including significant contributions by Mélanie Hébert et al., highlights the potential of CDCC and CCI to quantify both the number and severity of complications in adult cardiac surgery. Their utility in this specialized field presents opportunities for robust data collection and outcome evaluation. Conclusion: While the application of CDCC and CCI in cardiac surgery shows promise, the notable scarcity of comprehensive evaluation studies has hindered the accessibility of these systems to clinicians. This study provides a clear and accessible reference for healthcare professionals seeking to integrate CDCC and CCI into their cardiac surgery practice. Additionally, we propose the need for guideline studies to address this gap in the field.

FROM NOTHING TO SOMETHING: TALE OF UNRAVELING THE SECRET TO SUCCESS OF A NEOPHYTE CRIMINOLOGIST IN TAKING LICENSURE EXAM

This phenomenological study aimed to fathom the tale of unravelling the secret to the success of neophyte criminologists in passing the licensure examination. The study utilized a qualitative research design using a phenomenological approach, with 18 criminologists from Ramon Magsaysay Memorial College, General Santos City, chosen through purposive sampling. Thematic analysis was used as a data analysis tool. In light of this, results revealed the themes developed wherein this also discovered that the secret to the success of criminologists in taking and passing the CLE where they experienced mixed emotions, very challenging, stressful phenomena, feelings of nervousness, lack of preparation, frustrating events, remaining hopeful and positivism helps. In addition, criminologists experienced challenges like time constraints, financial problems, no face-to-face review, sleepless nights, anxiety situations and restrictions during the pandemic. On the coping mechanisms, criminologists pray harder, seek help, manage time well, rest when necessary, study hard, boost self-esteem, enrol in a review centre and practice the elimination methods. Furthermore, criminologists’ insights or realization revealed that preparation is necessary: take the review seriously, join a group study, give your best shot, surpass trials, increase faith and prioritize well-being. Taking a criminologist licensure exam requires extensive preparation and perseverance as they will encounter many challenges before they pass it. The insights learned by the neophyte criminologists make them more competent as professionals in their field of specialization.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/soc/0787/a.php" alt="Hit counter" /&gt;&lt;/p&gt;

Value and Role of Obesity and Metabolic Surgery in the Study of Human Medicine, Academic Teaching and Advanced Training

In teaching, obesity and metabolic surgery play only a limited role. However, due to the rapidly increasing number of surgical interventions, communication of knowledge in the study of human medicine as well as in gastroenterological and surgical residency (general and abdominal surgery) is required.Narrative review. · Currently, lectures on obesity and metabolic surgery do not belong to the current surgical curriculum of human medicine at all University Medical Schools, which needs to be absolutely established step by step - based on their topicality and importance in the clinical spectrum of clinical care.. · This rapidly developing special area of abdominal surgery is characterized by specific and diverse interdisciplinarity.. · Multimorbidity, changes in resorption mechanisms but also psychological changes have a substantial impact on the indication and patient outcome.. · The increase in endoscopic, surgical and also robotic interventions and surgical methods in this special field requires a broad knowledge of all surgical disciplines in intervention preparation, perioperative and follow-up management of obesity-associated basic diagnosis. This objective is important even in the study of human medicine and further advanced training.. The inclusion of such complex contents on obesity and metabolic surgery into surgical teaching and into residency of general and abdominal surgery is essential to be future-oriented and prepared for the development of the discipline.