2025 ILC Annual International Conference , 16th & 17 June, 2025, Genoa, Italy, Global Collaboration,Local Action for Fundamentals of Care Innovation. Zie bladzijde 81. An international group of experts has joined forces for the further development of Artificial Intelligence (AI) in relation to the Fundamentals of Care (FoC) framework. AI, or its categories like machine learning and deep learning, offers potential to identify patterns in healthcare data, develop clinical prediction models, and derive insights from large datasets. For example, algorithms can be created to detect the start of the palliative phase based on electronic health records, or to inform nursing decisions based on lifestyle monitoring data for older adults. These AI applications significantly influence nurses' roles, the nurse-client relationship and nurses’ professional identity. Consequently, nurses must take responsibility to ensure that AI applications align with person-centered fundamental care, professional ethics, equity, and social justice. Thus, nursing leadership is essential to lead the development and use of AI applications that support nursing care according to the FoC framework, and enhance patient outcomes. The aim of the current project is to explore nurses’ responsibility for how AI adds value to the FoC framework. Firstly, nurse leaders play a vital role in overseeing the quality and relevance of data collected in daily practice, as these data are foundational for AI algorithms. The elements as articulated in the FoC framework should be the building blocks for any algorithm. These building blocks can be linked to clinical and social conditions, and life stages, building from the basis of the individual's human needs. Secondly, it is crucial for nurses to participate in the interdisciplinary teams that develop AI algorithms. Their participation and expertise ensure that algorithms are co-created with an understanding of the needs of their clients, maximizing the potential for positive outcomes. In addition to education, policy, and regulation, a nurse-led, interdisciplinary research program is needed to investigate the relationship between AI applications, the FoC framework and it’s impact on nurse-client relationships, nurses’ professional identity, and patient outcomes.
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Gedachten over verandering voor een traditionele Russische lerarenopleiding.
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In our current and turbulent times, it is clear that some sort of organisational agility, in which-ever way achieved, is necessary to survive and thrive as an organisation. The question is how to achieve such manoeuvrability. We propose the use of design (thinking), with a focus on prototyping to iteratively develop greater organisational agility. Based on literature research into the circumstance that drive change, design, prototyping and a number of organisations that seem to have incorporated the right tactics, as well as observations made at a change-programme for a large Dutch corporate, we have developed a model to guide this process. The model proposes that an organisation should focus on developing a shared sense of purpose, to guide all its undertakings. Afterwards, employees should collaborate on iteratively creating the right (digital & physical) environments, culture and personal grounding for them and the organisation, to be able to achieve this purpose. Based on certain (dynamic) criteria and these various domains, personal responsibilities (action agendas) may constantly evolve and keep the organisation agile. This paper explains the reasoning behind the model and calls for further experimentation to take place to verify its effectiveness. LinkedIn: https://www.linkedin.com/in/christine-de-lille-8039372/
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An overview of fundamentals, best practices and a tutorial.
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This review offers a detailed examination of the current landscape of radio frequency (RF) electromagnetic field (EMF) assessment tools, ranging from spectrum analyzers and broadband field meters to area monitors and custom-built devices. The discussion encompasses both standardized and non-standardized measurement protocols, shedding light on the various methods employed in this domain. Furthermore, the review highlights the prevalent use of mobile apps for characterizing 5G NR radio network data. A growing need for low-cost measurement devices is observed, commonly referred to as “sensors” or “sensor nodes”, that are capable of enduring diverse environmental conditions. These sensors play a crucial role in both microenvironmental surveys and individual exposures, enabling stationary, mobile, and personal exposure assessments based on body-worn sensors, across wider geographical areas. This review revealed a notable need for cost-effective and long-lasting sensors, whether for individual exposure assessments, mobile (vehicle-integrated) measurements, or incorporation into distributed sensor networks. However, there is a lack of comprehensive information on existing custom-developed RF-EMF measurement tools, especially in terms of measuring uncertainty. Additionally, there is a need for real-time, fast-sampling solutions to understand the highly irregular temporal variations EMF distribution in next-generation networks. Given the diversity of tools and methods, a comprehensive comparison is crucial to determine the necessary statistical tools for aggregating the available measurement data.
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