BJAS & JAIR (Journals)
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Secondary Nomination and Co-Referencing of Medical Terms in the Strategy of Harmonizing Indicators of Knowledge Assimilation in the Doctor\u27s Portfolio
Get PDFSome issues of the formation of the portfolio of doctors during continuous professional development are considered. Particular attention is paid to the peculiarities of the evaluation of the analyzed information, in particular, the problems of secondary nomination and co-referentiality of medical terms. The purpose of the study was to substantiate the prerequisites for creating a new type of portfolio by using methods of intellectual analysis of multidimensional information, as well as the formation of models and cognitive structures, which should become a central event in person-oriented active learning. It is shown that in order to ensure an adequate mechanism for evaluating multidimensional information in the doctors\u27 portfolio, it is advisable to use ensembles of algorithms for intelligent analysis of big data. Conclusions: 1. The portfolio of doctors and pharmacists is of exceptional importance for the functioning of the system of continuous professional development of the relevant specialists. It helps organize lifelong learning and allows you to keep all evidence of learning and professional activity. 2. Taking into account the importance of the portfolio, it should be capable of standardized and formally calculated evaluation. 3. The entry of information into the portfolio is preceded by the determination of the semantic equivalence of the available information regarding the acquisition and assimilation of knowledge. 4. It is proposed to use ensembles of approaches to the analysis and arrangement of information in the portfolio - a combination of several algorithms that function simultaneously and provide an opportunity to correct possible errors. 5. The proposed decision-making algorithm during the preliminary analysis of information for the portfolio
Bias – The Achilles Heel of Artificial Intelligence in Healthcare
No full textThe field of artificial intelligence (AI) has evolved considerably since the end of the 20th century. While this technology shows great promise and potential to solve daily tasks, the question of fairness of decisions by AI models needs to be addressed. There have been examples of AI models performing unfair and prejudiced decisions which has led to a growing need to be able to know ‘why’ and ‘how’ these models make decisions. This is particularly important in the healthcare field, where the outcomes of AI models play a decisive role in the well-being of patients. In addition, a system for detecting and mitigating biases needs to be developed so that the advantages of AI can be utilized in healthcare. A scoping review was carried out to study the source, nature and impact of biases of AI models. Results showed that bias can be data-driven, algorithmic or introduced by humans. These biases propagate deeply rooted societal inequality, misdiagnose patient groups, and further perpetuate global health inequity. Mitigation of biases is proposed at the various stages of the machine learning pipeline. These strategies use techniques such as scrutinizing the way data is collected, better representation of patient groups, optimal training of the model and evaluating model performance. In conclusion, it must be ascertained that AI decisions are free of unwarranted biases and justly fair. Therefore, in an effort to mitigate bias, AI models should adopt systems that contain techniques in which biases can be predicted, measured, explained and then mitigated
Transforming Healthcare: Bridging Digital Maturity, Health Data, and Global Policy
Get PDFThe session “Transforming Healthcare: Bridging Digital Maturity, Health Data, and Global Policy,” held at the DigiHealthDayS 2024 in Pfarrkirchen, Bavaria, Germany, examined how digital transformation can create measurable value in healthcare. Hosted by Angela Ahrendt (FTI Consulting) and Armin Scheuer (Lemonmint), the session featured a keynote by Hal Wolf (HIMSS) and contributions on digital maturity in healthcare, digital health literacy and the European Health Data Space (EHDS). Discussions emphasized the role of data-driven decision-making, interoperability, and policy frameworks in shaping a sustainable digital health ecosystem. The session underscored that true innovation emerges when technology, policy, and strategy align to enhance patient outcomes and system efficiency
Assessment of the Possibility of Implementing the Strategy of Information Integration of Health Care Systems
Get PDFThis study considers the problems of globalization of medical education and practical health-care in consideration of the wide implementation of information technologies. The creation of unified educational medical systems is hindered by many factors, among which the most important are the lack of standardized technological platforms and educational programs, assessment processes, andmost importantly, data processing methodology. The purpose of the study was to assess the possibility of integrating health-care information at the current stage of information systems development, in order to support future medical education. Conclusions: 1. The creation of a single integrated health-care system on a global scale seems unlikely today. We can only talk about the extent of harmonization of the relevant systems through the interoperability of their data. 2. The constant avalanche-like growth of data dictates the continuous growth of data management problems. At the same time, the right combination of localization, adaptation to cultural diversity and technologies, in the context of sufficient resources and adequate infrastructure in specific countries, is extremely necessary
Continuing Education Measures for the Development of Future Skills at Universities: A Summary of the Empirical Analysis for East Bavaria in the Context of the Changing World of Work
Get PDFThe dynamic work environment increasingly necessitates the development of Future Skills, pivotal competencies attainable through part-time further education at universities. In East Bavaria, a rural region marked by diverse challenges, providers of further education should devise measures to impart Future Skills, with innovative didactic methods playing a crucial role. This study analyzes the needs of professionals in the region, deriving concepts for academic training. A quantitative online survey involving 396 East Bavarian participants identifies key Future Skills, providing initial guidelines for further education. Survey results are condensed and expanded through a mixed-methods approach, incorporating qualitative insights from interviews with five experts. Resilience, dialogue and conflict competency, problem-solving ability, and digital literacy emerge as central Future Skills. Developing training for these competencies should consider diverse target group needs. Recommended are short, three-month blended learning formats without prerequisites or with relevant professional experience. Didactic approaches should emphasize practical relevance, transferability, and action orientation. Problem- and project-based methods, promoting exchange, are suitable, and a methodological mix can support Future Skills development. The role of educators is evolving towards mentors and coaches. This work substantiates existing theories and empirical evidence on target group orientation and didactic methods, providing insights for further research and practical applications. It is recommended that universities expand Future Skills training offerings and facilitate a combination of formal and informal programs for increased flexibility. The dynamic work environment increasingly necessitates the development of future skills, pivotal competencies attainable through part-time continuing education at universities. In East Bavaria, a rural region marked by diverse challenges, providers of continuing education should devise measures to impart future skills, with innovative didactic methods playing a crucial role. This study analyzes the needs of professionals in the region, deriving concepts for academic training. A quantitative online survey involving 396 East Bavarian participants identifies key future skills, providing initial guidelines for continuing education. Survey results are condensed and expanded through a mixed methods approach, incorporating qualitative insights from interviews with five experts. Resilience, dialogue and conflict competency, problem-solving ability, and digital literacy emerge as central future skills. The development of training for these competences should take into account the different needs of the target groups. Short, three-month blended learning formats without prerequisites or with relevant professional experience are recommended. Didactic approaches should emphasize practical relevance, transferability, and action orientation. Problem- and project-based methods, promoting exchange, are suitable, and a methodological mix can support future skills development. The role of educators is evolving towards mentors and coaches. This work substantiates existing theories and empirical evidence on target group orientation and didactic methods, providing insights for further research and practical applications. It is recommended that universities expand future skills training offerings and facilitate a combination of formal and informal programs for increased flexibility.
Die dynamische Arbeitswelt erfordert zunehmend die Entwicklung von Future Skills, die durch berufsbegleitende Weiterbildung an Hochschulen erworben werden können. In Ostbayern, einer ländlich geprägten Region mit vielfältigen Herausforderungen, sind Weiterbildungsanbieter aufgefordert, Maßnahmen zur Vermittlung von Future Skills zu konzipieren, wobei innovative didaktische Methoden eine entscheidende Rolle spielen. Die vorliegende Studie analysiert den Bedarf der Fachkräfte in der Region und leitet daraus Konzepte für die wissenschaftliche Weiterbildung ab. In einer quantitativen Online-Befragung mit 396 Teilnehmerinnen und Teilnehmern aus Ostbayern werden wesentliche Future Skills für die Zukunft identifiziert und erste Ansätze zur Konzeption von Weiterbildungsmaßnahmen abgeleitet. Die Ergebnisse der Befragung werden im Sinne eines sequenziellen und integrativen Vorgehens im Mixed-Methods-Ansatz mit einer qualitativen Studie verdichtet und erweitert, wobei qualitative Erkenntnisse aus
Interviews mit fünf Experten berücksichtigt werden. Als zentrale Future Skills kristallisieren sich Resilienz, Dialog- und Konfliktfähigkeit, Lösungsfähigkeit und Digital Literacy heraus. Bei der Entwicklung von Weiterbildungsmaßnahmen für diese Kompetenzen sollten vielfältige Bedürfnisse der Zielgruppe berücksichtigt werden. Empfehlenswert sind kurze, maximal dreimonatige Blended-Learning-Formate ohne Vorkenntnisse oder mit einschlägiger Berufserfahrung. Bei den didaktischen Ansätzen sollten Praxisbezug und -transfer sowie Handlungsorientierung zentral sein. Problem- und projektorientierte Methoden, die den Austausch fördern, sind geeignet, und ein Methodenmix kann die zukünftige Kompetenzentwicklung unterstützen. Die Rolle der Lehrenden entwickelt sich hin zu Lernbegleitern und Coaches. Die vorliegende Arbeit untermauert bereits existierende Theorien und empirische Belege zur Zielgruppenorientierung sowie zu didaktischen Methoden und liefert Erkenntnisse für die weitere Forschung und die praktische Anwendung. Es wird empfohlen, dass die Hochschulen ihr Angebot an wissenschaftlicher Weiterbildung erweitern und eine Kombination aus formellen und informellen Programmen anbieten, um die Flexibilität zu steigern
Vector Diagnosis of Patient Conditions in Telemedicine
Get PDFTelemedicine is a rapidly growing field in healthcare, offering wide-ranging opportunities to address various challenges faced by healthcare workers and patients. Despite its many benefits for both patients and healthcare providers, there are still a number of unresolved issues. This study aims to explore the potential of telemedicine by conceptualizing it as the interplay of two vectors: the patient\u27s condition and technological readiness for consultation.Research Objectives. The patient\u27s condition vector includes physiological, biochemical, and clinical indicators. The technological readiness vector is defined by the treating physician\u27s competence, the consultant\u27s expertise, modern information processing capabilities, and the availability of necessary time, among other factors.Conclusions. 1. Telemedicine consultations require a robust real-time medical data management system that allows consultants and attending physicians to efficiently process data, retain validated data for patient-specific recommendations, and enhance the global telemedicine framework with decision-making expertise. 2. Integrating big data analytics can improve the prediction and identification of disease diagnoses and prognoses, aiding in the development of effective strategies for complication prevention and disease treatment. Real-time communication with each patient and complex data processing can only be achieved through artificial intelligence. Manual intervention is insufficient for serving thousands of users simultaneously. 3. It\u27s crucial during telemedicine consultations to consider not only the static indicators of the patient\u27s condition but also their baseline data, stable condition indicators from previous studies, and personalized correlation galaxies. Recommendations based solely on the analysis of the patient\u27s status during the telemedicine session risk incorrect conclusions. 4. Biosemiotics, which focuses on the language and rules of signals and codes in biological systems, combines ideas from systems theory, information theory, and linguistics. This integration may offer a new perspective on the classification and interpretation of biological and medical signaling. A coherent theory of biosemiotics needs to be developed.
A Scoping Review of the Role of Clinical Decision Support Systems in Intensive Care Units during the COVID-19 Pandemic
Get PDFDuring the COVID-19 pandemic, clinical decision support systems (CDSS) have been increasingly instrumental in reshaping the intensive care unit (ICU) landscape. This paper highlights the importance of CDSS in improving healthcare professionals\u27 decision-making processes by examining their numerous contributions to the management of critically ill patients.This scoping review comprised information concerning the role of CDSS in ICUs during the COVID-19 pandemic and lessons for the future of public health care (PHC). The identified literature was published during the COVID-19 peak years (2019–2023), retrieved from the Cochrane Library, Embase, Medline, PubMed, CINAHL, Google Scholar and Scopus. A set of predefined inclusion criteria were used, then thematic analysis was applied. The reporting followed the PRISMA guidelines for scoping reviews.A total of 9 studies were included in the final synthesis (all articles). These studies examined various aspects of the role of CDSS in ICUs during the COVID-19 pandemic. The scoping review was comprehensive and focused on the emerging topic of discussion but lacked risk of bias assessment.In the midst of the COVID-19 pandemic\u27s unparalleled obstacles, CDSS in ICUs became a vital resource for medical professionals. These technologies help physicians diagnose, treat, and manage COVID-19 patients by using innovative algorithms and real-time data analytics. Early identification, monitoring, timely alarms, and insights into patients\u27 changing clinical status are some of the most crucial functions of CDSS. This capacity was vital in quickly recognising conditions that were getting worse, facilitating quick action, and enhancing patient outcomes.Additionally, CDSS in ICUs proved effective in therapy guiding, providing evidence-based suggestions for therapeutic approaches. Through the integration of patient information, test findings, and established procedures, these systems enabled tailored and efficient treatment, guaranteeing that medical interventions corresponded with the dynamic course of the illness. Moreover, CDSS helped with risk classification, which enabled medical practitioners to carefully manage resource allocation and customise interventions based on the unique profiles of each patient.Through the reduction of errors and improvement of patient safety, CDSS was significant in the field of drug management. These technologies met the vital requirement for accuracy in COVID-19 patient care by providing notifications for drug interactions, dosage modifications, and medication administration.The extensive capabilities that were required in the ICU highlight the revolutionary influence on healthcare delivery that CDSS have. CDSS was invaluable in navigating the challenges of caring critically sick patients in the demanding setting of the global health crisis by integrating evidence-based practices, optimising resource utilisation, and offering real-time decision support
Innovative Databases in Ecomonitoring Information Systems: Images of Genetic Codes as Keys
Get PDFIntroduction: Images of biological objects are used very often now for the creation of novel information systems for biology and medicine. But the sphere of their use, tasks which are possible to solve with them, can be successfully expanded.Problem statement: Contemporary biomedical relational databases (DBs) very often include images. But additionally, images themselves can play important functional roles in DBs. Purpose: To use images of fishes’ genetic codes fragments as keys for the construction of relational DB; this has to ensure the reliability of biomedical information storage better than in prototypes, and to provide better data integrity. Methods: DB Design, object-oriented system analysis for DBs design in an optimal way, ER diagrams design.Results: An algorithm for the construction of relational DBs with images, other biomedical information, analytical approaches and recommendations for doing this in an optimal way were presented. The main attention was paid to the creation and application of the most functionally high-quality codes for keys in DB (including primary keys). To perform this function, usages of codes based on images of fishes’ genetic codes fragments were proposed. The example for such a task solution, described in this article, was the creation of DBs with information about fishes (or other aquatic organisms) and chemical inorganic environmental pollutants which affected them. Conclusions: The results of the use of images of genetic codes fragments as keys for the construction of DBs with ecological data in an information system for environmental monitoring were presented. Through the high level of individualization of the data in a system with such keys the maintenance of species-specific information is substantiated. The work has theoretical and practical values. It may also be applied in an academician process for teaching students
Advancing Healthcare: AI Integration, Interoperability and Sustainability Challenges
Get PDFThis article explores the evolving landscape of healthcare transformation through intelligent integration, focusing on artificial intelligence (AI), interoperability, and sustainability in the digital era. This analysis thoroughly investigates various aspects, including patient-centric immunization systems, blockchain-based e-health management, resource optimization, and adaptable clinical solutions. The investigation is framed around evolving healthcare considerations, emphasizing a thorough exploration of advancements, comparisons, and challenges encountered in the implementation of intelligent and integrated healthcare systems. The conclusion provides valuable insights for healthcare professionals and policymakers, guiding the development of a more connected and intelligent healthcare ecosystem