Specific Knowledge Base Research Articles

Enhancing Orthopedic Knowledge Assessments: The Performance of Specialized Generative Language Model Optimization.

This study aimed to evaluate and compare the effectiveness of knowledge base-optimized and unoptimized large language models (LLMs) in the field of orthopedics to explore optimization strategies for the application of LLMs in specific fields. This research constructed a specialized knowledge base using clinical guidelines from the American Academy of Orthopaedic Surgeons (AAOS) and authoritative orthopedic publications. A total of 30 orthopedic-related questions covering aspects such as anatomical knowledge, disease diagnosis, fracture classification, treatment options, and surgical techniques were input into both the knowledge base-optimized and unoptimized versions of the GPT-4, ChatGLM, and Spark LLM, with their generated responses recorded. The overall quality, accuracy, and comprehensiveness of these responses were evaluated by 3 experienced orthopedic surgeons. Compared with their unoptimized LLMs, the optimized version of GPT-4 showed improvements of 15.3% in overall quality, 12.5% in accuracy, and 12.8% in comprehensiveness; ChatGLM showed improvements of 24.8%, 16.1%, and 19.6%, respectively; and Spark LLM showed improvements of 6.5%, 14.5%, and 24.7%, respectively. The optimization of knowledge bases significantly enhances the quality, accuracy, and comprehensiveness of the responses provided by the 3 models in the orthopedic field. Therefore, knowledge base optimization is an effective method for improving the performance of LLMs in specific fields.

Beyond Index Conditions: Applying a Multimorbidity Approach to Renal Cancer Nursing

ObjectiveThis article aims to describe the key components of renal cancer nursing and multimorbidity nursing, and reflects on how adopting a multimorbidity approach to renal cancer nursing can help nurses provide holistic patient care. MethodsThis is a discussion paper drawing on relevant evidence and theory. ResultsRenal cancer nurses have a highly specialised knowledge base and are able to use this expertise to deliver excellent care to people with cancer. However, lots of people with cancer have other conditions as well. Adopting a multimorbidity approach to nursing care provides a more holistic framework for care delivery. ConclusionsCancer nurses are ideally placed to support patients in this way, so they are able to deliver care which accounts for factors such as treatment burden and how this impacts on patients and carers. Implications for nursing practiceNurses who care for people with renal cancer should view their patients through the lens of multimorbidity. This involves screening for other chronic conditions, considering polypharmacy, providing emotional support and continuity of care, and coordinating care in a way that accounts for the potentially burdensome nature of the patient's interactions with health care.

Perceptions and Lived Experiences of Nurses After Completion of a Perinatal Nurse Residency Program.

This study was designed to explore the perceptions and lived experiences of new graduate or new-to-specialty labor and delivery nurses. These nurses had completed a perinatal nurse residency program at a high-risk metropolitan medical center in the Pacific Northwest region of the United States. Eight nurses were interviewed for this study with qualitative individual interviews. Qualitative content analysis was used. Three main themes emerged: assimilating a specialized knowledge base and skill sets, navigating challenging circumstances, and coping with the transition to independence. Nurse residency programs can ease the transition to practice in the labor and delivery specialty. Revisions to future perinatal residency programs should include enhanced preceptor education, prolonged night shift orientation, assessment of nurse learning style and needs, and increased consistency of debriefing after traumatic events. [J Contin Educ Nurs. 202x;5x(x):xx-xx.].

Introducing ChatSQC: Enhancing statistical quality control with augmented AI

We introduce ChatSQC, an innovative chatbot system that combines the power of OpenAI’s Large Language Models (LLM) with a specific knowledge base in Statistical Quality Control (SQC). Our research focuses on enhancing LLMs using specific SQC references, shedding light on how data preprocessing parameters and LLM selection impact the quality of generated responses. By illustrating this process, we hope to motivate wider community engagement to refine LLM design and output appraisal techniques. We also highlight potential research opportunities within the SQC domain that can be facilitated by leveraging ChatSQC, thereby broadening the application spectrum of SQC. A primary goal of our work is to provide a template and proof-of-concept on how LLMs can be utilized by our community. To continuously improve ChatSQC, we ask the SQC community to provide feedback, highlight potential issues, request additional features, and/or contribute via pull requests through our public GitHub repository. Additionally, the team will continue to explore adding supplementary reference material that would further improve the contextual understanding of the chatbot. Overall, ChatSQC serves as a testament to the transformative potential of AI within SQC, and we hope it will spur further advancements in the integration of AI in this field.

From specialized knowledge frames to linguistically based ontologies

This paper explains conceptual modeling within the framework of Frame-Based Terminology (Faber, 2012; 2015; 2022), as applied to EcoLexicon (ecolexicon.ugr.es), a specialized knowledge base on the environment (León-Araúz, Reimerink &, Faber, 2019; Faber & León-Araúz, 2021). It describes how a frame-based terminological resource is currently being restructured and reengineered as an initial step towards its formalization and subsequent transformation into an ontology. It also explains how the information in EcoLexicon can be integrated in environmental ontologies such as ENVO (Buttigieg, Morrison, Smith, Mungall & Lewis, 2013; Buttigieg, Pafilis, Lewis, Schildhauer, Walls & Mungall, 2016), particularly at the bottom tiers of the Ontology Learning Layer Cake (Cimiano, 2006; Cimiano, Maedche, Staab & Volker, 2009). The assumption is that frames, as a conceptual modeling tool, and information extracted from corpora can be used to represent the conceptual structure of a specialized domain.

Enriching the FIDEO ontology with food-drug interactions from online knowledge sources

The increasing number of articles on adverse interactions that may occur when specific foods are consumed with certain drugs makes it difficult to keep up with the latest findings. Conflicting information is available in the scientific literature and specialized knowledge bases because interactions are described in an unstructured or semi-structured format. The FIDEO ontology aims to integrate and represent information about food-drug interactions in a structured way. This article reports on the new version of this ontology in which more than 1700 interactions are integrated from two online resources: DrugBank and Hedrine. These food-drug interactions have been represented in FIDEO in the form of precompiled concepts, each of which specifies both the food and the drug involved. Additionally, competency questions that can be answered are reviewed, and avenues for further enrichment are discussed.

Using occupational therapy principles and practice to support independent message generation by individuals using AAC instead of facilitated communication

Facilitated communication (FC) has been a heavily debated and documented topic across multiple disciplines, including sociology, education, psychology, pediatrics, speech-language pathology, and disability studies. Although many professionals from various disciplines and advocates have offered opinions, suggestions, and research on the topic, there has been minimal input from the occupational therapy (OT) profession. The lack of OT input is noteworthy as OTs are experts in enabling upper extremity performance and independence through a variety of training, adaptation and modification strategies, and use of external supports. Because of their professional code of ethics and a specific knowledge base, OTs are uniquely positioned to provide a host of ethical and evidence-based strategies that enable independent access to communication technology. The consideration of multiple access options is contrary to the typical facilitated encounter where facilitators exclusively choose to manipulate an upper extremity in order for letters to be selected on a display or keyboard. The purpose of this paper is threefold: (a) To offer insight into the standard of care by OTs including their ethical standards; (b) to identify varied accommodations that enable access using a feature-matching standard of care that eliminates the need for a facilitator; and (c) to highlight how to increase independent assistive technology/augmentative and alternative communication access, thus dissuading the need or use of facilitated access to letters.

Truth and Reconciliation in Medical Schools: Forging a Critical Reflective Framework to Advance Indigenous Health Equity.

In 2015, the Truth and Reconciliation Commission (TRC) of Canada outlined 94 Calls to Action, which formalized a responsibility for all people and institutions in Canada to confront and craft paths to remedy the legacy of the country's colonial past. Among other things, these Calls to Action challenge medical schools to examine and improve existing strategies and capacities for improving Indigenous health outcomes within the areas of education, research, and clinical service. This article outlines efforts by stakeholders at one medical school to mobilize their institution to address the TRC's Calls to Action via the Indigenous Health Dialogue (IHD). The IHD used a critical collaborative consensus-building process, which employed decolonizing, antiracist, and Indigenous methodologies, offering insights for academic and nonacademic entities alike on how they might begin to address the TRC's Calls to Action. Through this process, a critical reflective framework of domains, reconciliatory themes, truths, and action themes was developed, which highlights key areas in which to develop Indigenous health within the medical school to address health inequities faced by Indigenous peoples in Canada. Education, research, and health service innovation were identified as domains of responsibility, while recognizing Indigenous health as a distinct discipline and promoting and supporting Indigenous inclusion were identified as domains within leadership in transformation. Insights are provided for the medical school, including that dispossession from land lays at the heart of Indigenous health inequities, requiring decolonizing approaches to population health, and that Indigenous health is a discipline of its own, requiring a specific knowledge base, skills, and resources for overcoming inequities.

A Context-based Chatbot Surpasses Trained Radiologists and Generic ChatGPT in Following the ACR Appropriateness Guidelines.

Background Radiological imaging guidelines are crucial for accurate diagnosis and optimal patient care as they result in standardized decisions and thus reduce inappropriate imaging studies. Purpose In the present study, we investigated the potential to support clinical decision-making using an interactive chatbot designed to provide personalized imaging recommendations from American College of Radiology (ACR) appropriateness criteria documents using semantic similarity processing. Methods We utilized 209 ACR appropriateness criteria documents as specialized knowledge base and employed LlamaIndex, a framework that allows to connect large language models with external data, and the ChatGPT 3.5-Turbo to create an appropriateness criteria contexted chatbot (accGPT). Fifty clinical case files were used to compare the accGPT's performance against general radiologists at varying experience levels and to generic ChatGPT 3.5 and 4.0. Results All chatbots reached at least human performance level. For the 50 case files, the accGPT performed best in providing correct recommendations that were "usually appropriate" according to the ACR criteria and also did provide the highest proportion of consistently correct answers in comparison with generic chatbots and radiologists. Further, the chatbots provided substantial time and cost savings, with an average decision time of 5 minutes and a cost of 0.19 € for all cases, compared to 50 minutes and 29.99 € for radiologists (both p < 0.01). Conclusion ChatGPT-based algorithms have the potential to substantially improve the decision-making for clinical imaging studies in accordance with ACR guidelines. Specifically, a context-based algorithm performed superior to its generic counterpart, demonstrating the value of tailoring AI solutions to specific healthcare applications.

Оптическая сеть реального времени в задачи авионики

This study analyzes existing approaches to building fault-tolerant onboard systems at the hardware and software levels. The main advantages of constructing an Avionics Integrated Vehicle System (AIVS) based on fiber optic components are considered, particularly for deploying a Unified Intelligent System (UIS) that provides intelligent decision-making in case of abnormal situations. Scenarios for countering various abnormal situations at different levels of aircraft equipment complex (AEC) operation are developed, aiming to enhance the fault tolerance of its systems and, consequently, flight safety as a whole. Algorithms for reconfiguring the AIVS in case of abnormal situations, both during flight and on the ground, are devised. Principles for creating a specialized knowledge base for information support (KBIS) based on operational documentation are proposed. Logical programming methods are employed to simplify the formalization of knowledge stored in the KBIS and to facilitate modification and supplementation of the KBIS with new data. Calculation methodologies for AIVS configuration characteristics based on the KBIS are developed. Dynamic synthesis methods for generating new AIVS configurations are designed to address abnormal situations arising during aircraft operation. State space information formalized using logical programming methods is used to solve the synthesis problem. A complete system graph is constructed considering its redundancy, and a search-synthesis for the most suitable AIVS architecture capable of countering failures is performed.

NAFLDkb: A Knowledge Base and Platform for Drug Development against Nonalcoholic Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease with a broad spectrum of histologic manifestations. The rapidly growing prevalence and the complex pathologic mechanisms of NAFLD pose great challenges for treatment development. Despite tremendous efforts devoted to drug development, there are no FDA-approved medicines yet. Here, we present NAFLDkb, a specialized knowledge base and platform for computer-aided drug design against NAFLD. With multiperspective information curated from diverse source materials and public databases, NAFLDkb presents the associations of drug-related entities as individual knowledge graphs. Practical drug discovery tools that facilitate the utilization and expansion of NAFLDkb have also been implemented in the web interface, including chemical structure search, drug-likeness screening, knowledge-based repositioning, and research article annotation. Moreover, case studies of a knowledge graph repositioning model and a generative neural network model are presented herein, where three repositioning drug candidates and 137 novel lead-like compounds were newly established as NAFLD pharmacotherapy options reusing data records and machine learning tools in NAFLDkb, suggesting its clinical reliability and great potential in identifying novel drug-disease associations of NAFLD and generating new insights to accelerate NAFLD drug development. NAFLDkb is freely accessible at https://www.biosino.org/nafldkb and will be updated periodically with the latest findings.

РАЗРАБОТКА И АПРОБАЦИЯ ПРОТОТИПА ЭКСПЕРТНОЙ СИСТЕМЫ ДЛЯ ДИАГНОСТИКИ ПОДАГРЫ

Significance. Gout is a rheumatological disease that affects up to 2% of the population of the Russian Federation according to various sources. The pathogenesis of the disease is associated with a disturbance in uric acid metabolism and manifests itself in the deposition of monosodium urate crystals in various tissues of the body. Timely diagnosis and treatment of the disease can prevent the development of gout complications and disability of the patient, however, according to various sources, it takes from 44 to 8 years to diagnose gout. One possible way to improve the quality of gout diagnosis is to develop and implement an expert system for preliminary diagnosis, diagnostic techniques and consultations, and final diagnosis. The purpose of the study is to develop and test a prototype expert system for gout diagnosis. Material and methods. The study used system analysis methods, including decomposition, analysis and synthesis methods, knowledge engineering methods, including knowledge representation methods (frames, semantic networks), ontological approach, fuzzy logic, hierarchical structuring methods and effective evaluation methods, including ROC analysis. Results. A prototype expert system for gout diagnosis has been developed. The prototype consists of a knowledge base, a logical solver, and an explanation subsystem. A specialized knowledge base editor was created for the development and subsequent maintenance of the knowledge base. The knowledge base was filled using 2 information objects jointly developed with a group of experts: the nomenclature of medical concepts (495 basic and 679 synonymous concepts) and logical schemes (40 schemes) related to gout diagnosis. The structure of the knowledge base is a combination of frames and semantic networks and includes 18 objects (7 types of concepts and 11 types of relationships). A graph database is used to store the knowledge base that determines the logic of the logical solver and the explanation subsystem. The logical solver analyzes the patient's clinical data and searches the optimal path, the end points of which are the recommendations of the expert system prototype. The explanation subsystem uses this path to argue the selected solution. The prototype expert system was tested on two depersonalized samples containing 1725 patients provided by the Tyumen Healthcare Department. Conclusion. A prototype expert system has been developed to determine the preliminary diagnosis of gout, prescribe diagnostic techniques and consultations for its verification, and make a final diagnosis. The prototype includes 1174 concepts and 5,640,522 relationships. Testing of the prototype expert system with ROC-analysis showed that its sensitivity was 91.3% CI [89.1%; 93.1%], specificity was 85.4% CI [82.9%; 87.6%], and AUROC was 0.954 CI [0.944; 0.963]. Scope of application. The research results can be used to integrate the prototype expert system into the doctor’s automated workplace of a medical information system in a medical organization.

The profession of social work: comparing Germany and Singapore

ABSTRACT Using a comparative approach the professional characteristics of social work in Germany and Singapore were analysed. The literature about the profession in both countries was reviewed according to eight criteria suggested by Weiss-Gal and Welbourne (The professionalisation of social work: A cross-national exploration. International Journal of Social Welfare, 17, 281–290, 2008): (1) public recognition, (2) monopoly over social care, (3) professional autonomy, (4) specific knowledge base, (5) educational system, (6) social work organisations, (7) code of ethics, and (8) status and prestige. Our analysis yielded similarities and differences in social work as a profession between the two countries. Common to Germany and Singapore is the existence of a body of knowledge, the professional training of social workers in higher education, the establishment of professional organisations, and the adoption of a code of ethics. The full definition of being a profession with respect to professional monopoly and autonomy is not reached by either one of the two countries. While extended education since the Bologna reform may lead to enhanced public recognition in Germany, relatively low salaries indicate a low status and prestige of the profession. In Singapore, the government just recently intentionally increased social workers’ remuneration to improve public recognition and to tackle social problems more effectively.

Shared Interoperable Clinical Decision Support Service for Drug-Allergy Interaction Checks: Implementation Study.

Clinical decision support (CDS) can improve health care with respect to the quality of care, patient safety, efficiency, and effectiveness. Establishing a CDS system in a health care setting remains a challenge. A few hospitals have used self-developed in-house CDS systems or commercial CDS solutions. Since these in-house CDS systems tend to be tightly coupled with a specific electronic health record system, the functionality and knowledge base are not easily shareable. A shared interoperable CDS system facilitates the sharing of the knowledge base and extension of CDS services. The study focuses on developing and deploying the national CDS service for the drug-allergy interaction (DAI) check for health care providers in Korea that need to introduce the service but lack the budget and expertise. To provide the shared interoperable CDS service, we designed and implemented the system based on the CDS Hooks specification and Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The study describes the CDS development process. The system development went through requirement analysis, design, implementation, and deployment. In particular, the concept architecture was designed based on the CDS Hooks structure. The MedicationRequest and AllergyIntolerance resources were profiled to exchange data using the FHIR standard. The discovery and DAI check application programming interfaces and rule engine were developed. The CDS service was deployed on G-Cloud, a government cloud service. In March 2021, the CDS service was launched, and 67 health care providers participated in the CDS service. The health care providers participated in the service with 1,008,357 DAI checks for 114,694 patients, of which 33,054 (3.32%) cases resulted in a "warning." Korea's Ministry of Health and Welfare has been trying to build an HL7 FHIR-based ecosystem in Korea. As one of these efforts, the CDS service initiative has been conducted. To promote the rapid adoption of the HL7 FHIR standard, it is necessary to accelerate practical service development and to appeal to policy makers regarding the benefits of FHIR standardization. With the development of various case-specific implementation guides using the Korea Core implementation guide, the FHIR standards will be distributed nationwide, and more shared interoperable health care services will be introduced in Korea.

Demonstrating institutional trustworthiness: A framework for pharmacy regulatory authorities.

Self-regulation is well suited for health care providers as the distinctive knowledge requirements can be effectively managed by those with the specific knowledge base compared to national or provincial/state governments. Despite their prevalence and long history in health care, self-regulating professions have become a topic of increasing debate as a result of evidence of declines in trust in a number of institutional contexts. It is important that Pharmacy Regulatory Authorities (PRAs), as the regulating body for a critical health profession, can demonstrate and proactively respond to issues related to public trust. Such capabilities are needed to address an overall decline in trust in self-regulated professions and allow PRAs to quickly address issues that may impact public trust within their own jurisdiction. However, a process and best practices that allow PRAs to demonstrate institutional trustworthiness to the public is lacking. Given the need from both a research and practice perspective, this research develops a conceptual framework of how PRAs can demonstrate institutional trustworthiness to the public. The literature was reviewed to identify dominant themes associated with regulatory practice that would serve to demonstrate institutional trustworthiness of PRAs to the public. Eight best practice themes emerged: public interest objective, transparency, engagement, accountability, independence, collaboration, adaptability, and awareness. The conceptual framework is comprised of six key steps, related to defining public interest orientation, implementing trust-related best practices, developing a communication strategy to increase public awareness of PRA activities, monitoring symbolic capital, assessing public trust in registrants (interpersonal trust), and assessing public and registrant trust in the regulator (institutional trust). Future research should develop pharmacy-focused instruments related to trust, establish baseline measures of registrant and public trust in pharmacy regulatory authorities, and explore issues of public trust in PRAs between different cultures and developed and developing countries.

A Novel Agricultural Machinery Intelligent Design System Based on Integrating Image Processing and Knowledge Reasoning

Agricultural machinery intelligence is the inevitable direction of agricultural machinery design, and the systems in these designs are important tools. In this paper, to address the problem of low processing power of traditional agricultural machinery design systems in analyzing data, such as fit, tolerance, interchangeability, and the assembly process, as well as to overcome the disadvantages of the high cost of intelligent design modules, lack of data compatibility, and inconsistency between modules, a novel agricultural machinery intelligent design system integrating image processing and knowledge reasoning is constructed. An image-processing algorithm and trigger are used to detect the feature parameters of key parts of agricultural machinery and build a virtual prototype. At the same time, a special knowledge base of agricultural machinery is constructed to analyze the test data of the virtual prototype. The results of practical application and software evaluation of third-party institutions show that the system improves the efficiency of intelligent design in key parts of agricultural machinery by approximately 20%, reduces the operation error rate of personnel by approximately 40% and the consumption of computer resources by approximately 30%, and greatly reduces the purchase cost of intelligent design systems to provide a reference for intelligent design to guide actual production.

Nurse's Role in Perioperative Neurological Evaluation and Management to Lower the Risk of Acute Stroke in Patients Undergoing Noncardiac, Nonneurological Surgery

Perioperative nurses have the opportunity to play a key role in prevention and recognition of stroke in patients undergoing noncardiac, nonneurological surgery and may impact this potentially devastating complication. Effective nursing care of the older adult requires a specialized knowledge base. Scientific Statements are a cornerstone of the knowledge base that informs this care. This article summarizes the recently released American Heart Association/American Stroke Association Scientific Statement entitled: Perioperative Neurological Evaluation and Management to Lower the Risk of Acute Stroke in Patients Undergoing Noncardiac, Nonneurological Surgery and discusses the nurse's role in the care of this vulnerable patient population.

Roy Adaptation Model: Theory-Based Knowledge and Nursing Care With a Person Experiencing COVID-19.

Nursing theories shed light and guide nursing care through provision of care to persons based on the specialized knowledge base of the profession. Nurses utilizing Roy's adaptation model deliver holistic care by accounting for people, processes, and the environments. The aim of this article is to illustrate the value of utilizing the Roy adaptation model in the care of a patients by reviewing nursing care provided to a patient diagnosed with COVID-19.

Erziehung als Grundbegriff der Pädagogik

Abstract Education as a Basic Concept of Pedagogy Education is defined as a basic concept of pedagogy against the background of the need for education and the ability of people to learn. Education reveals itself as a human practice consisting of two distinct but at the same time related operations. Education as a basic concept of pedagogy enables both the unity of the pedagogical discipline and profession as well as the contoured demarcation from neighboring human sciences and can thus emphasize the special knowledge base of pedagogy.

Adaptive tools for formation of the knowledge base of information and analytical system of training scientific staff

The author emphasizes the urgency of preserving the integrity of the scientific and educational process for the training of highly qualified personnel in higher education universities and research institutions. It is noted that the consequences of force majeure, including quarantine from the COVID-19 pandemic and the current martial law in Ukraine, cause some adjustments in the organization of training of scientific staff. In this regard, it is likely that the problem of creating a fundamentally new information-analytical system (IAS), which in this vector will include a specific knowledge base fol-lowing the requests of research users – subjects of scientific training. Thus, the article aims to present the results of the doctoral research, in particular on the intermediate content analysis of scientific, information and reference, educational and methodologi-cal and other literature sources and practice-oriented resources on the development of information technology and systems and their adaptive transfer, which will contribute to the accumulation of analytical information and its digitization. Emphasis is placed on the rationality of creation and use of intelligent IAS based on the formed specific knowledge bases using semantic technologies and ontological modelling. This is due to the existence of a large amount of diverse analytical information, based on which the issues of any research, which in the context of training is a mandatory component of sci-entific and educational activities of applicants for scientific education (undergraduates, graduate and doctoral researchers, etc.). It is claimed that a modern researcher will be able to master modern tools and expert technologies of information and analytical ac-tivities. A brief description of the adaptive tools with which the formation of a specific knowledge base in the IAS of training of scientific staff is presented. It is noted that se-mantic and ontological approaches are the most effective in this regard for building in-formation systems, in particular those related to the development of information-analytical competence of applicants for scientific education.