271 research outputs found
Automatic Generation of Personalized Recommendations in eCoaching
Denne avhandlingen omhandler eCoaching for personlig livsstilsstøtte i sanntid ved bruk av informasjons- og kommunikasjonsteknologi. Utfordringen er å designe, utvikle og teknisk evaluere en prototyp av en intelligent eCoach som automatisk genererer personlige og evidensbaserte anbefalinger til en bedre livsstil. Den utviklede løsningen er fokusert på forbedring av fysisk aktivitet. Prototypen bruker bærbare medisinske aktivitetssensorer. De innsamlede data blir semantisk representert og kunstig intelligente algoritmer genererer automatisk meningsfulle, personlige og kontekstbaserte anbefalinger for mindre stillesittende tid. Oppgaven bruker den veletablerte designvitenskapelige forskningsmetodikken for å utvikle teoretiske grunnlag og praktiske implementeringer. Samlet sett fokuserer denne forskningen på teknologisk verifisering snarere enn klinisk evaluering.publishedVersio
Measuring the impact of COVID-19 on hospital care pathways
Care pathways in hospitals around the world reported significant disruption during the recent COVID-19 pandemic but measuring the actual impact is more problematic. Process mining can be useful for hospital management to measure the conformance of real-life care to what might be considered normal operations. In this study, we aim to demonstrate that process mining can be used to investigate process changes associated with complex disruptive events. We studied perturbations to accident and emergency (A &E) and maternity pathways in a UK public hospital during the COVID-19 pandemic. Co-incidentally the hospital had implemented a Command Centre approach for patient-flow management affording an opportunity to study both the planned improvement and the disruption due to the pandemic. Our study proposes and demonstrates a method for measuring and investigating the impact of such planned and unplanned disruptions affecting hospital care pathways. We found that during the pandemic, both A &E and maternity pathways had measurable reductions in the mean length of stay and a measurable drop in the percentage of pathways conforming to normative models. There were no distinctive patterns of monthly mean values of length of stay nor conformance throughout the phases of the installation of the hospital’s new Command Centre approach. Due to a deficit in the available A &E data, the findings for A &E pathways could not be interpreted
Managing healthcare transformation towards P5 medicine (Published in Frontiers in Medicine)
Health and social care systems around the world are facing radical organizational, methodological and technological paradigm changes to meet the requirements for improving quality and safety of care as well as efficiency and efficacy of care processes. In this they’re trying to manage the challenges of ongoing demographic changes towards aging, multi-diseased societies, development of human resources, a health and social services consumerism, medical and biomedical progress, and exploding costs for health-related R&D as well as health services delivery. Furthermore, they intend to achieve sustainability of global health systems by transforming them towards intelligent, adaptive and proactive systems focusing on health and wellness with optimized quality and safety outcomes.
The outcome is a transformed health and wellness ecosystem combining the approaches of translational medicine, 5P medicine (personalized, preventive, predictive, participative precision medicine) and digital health towards ubiquitous personalized health services realized independent of time and location. It considers individual health status, conditions, genetic and genomic dispositions in personal social, occupational, environmental and behavioural context, thus turning health and social care from reactive to proactive. This requires the advancement communication and cooperation among the business actors from different domains (disciplines) with different methodologies, terminologies/ontologies, education, skills and experiences from data level (data sharing) to concept/knowledge level (knowledge sharing). The challenge here is the understanding and the formal as well as consistent representation of the world of sciences and practices, i.e. of multidisciplinary and dynamic systems in variable context, for enabling mapping between the different disciplines, methodologies, perspectives, intentions, languages, etc. Based on a framework for dynamically, use-case-specifically and context aware representing multi-domain ecosystems including their development process, systems, models and artefacts can be consistently represented, harmonized and integrated. The response to that problem is the formal representation of health and social care ecosystems through an system-oriented, architecture-centric, ontology-based and policy-driven model and framework, addressing all domains and development process views contributing to the system and context in question.
Accordingly, this Research Topic would like to address this change towards 5P medicine. Specifically, areas of interest include, but are not limited:
• A multidisciplinary approach to the transformation of health and social systems
• Success factors for sustainable P5 ecosystems
• AI and robotics in transformed health ecosystems
• Transformed health ecosystems challenges for security, privacy and trust
• Modelling digital health systems
• Ethical challenges of personalized digital health
• Knowledge representation and management of transformed health ecosystems
Table of Contents:
04 Editorial: Managing healthcare transformation towards P5
medicine
Bernd Blobel and Dipak Kalra
06 Transformation of Health and Social Care Systems—An
Interdisciplinary Approach Toward a Foundational
Architecture
Bernd Blobel, Frank Oemig, Pekka Ruotsalainen and Diego M. Lopez
26 Transformed Health Ecosystems—Challenges for Security,
Privacy, and Trust
Pekka Ruotsalainen and Bernd Blobel
36 Success Factors for Scaling Up the Adoption of Digital
Therapeutics Towards the Realization of P5 Medicine
Alexandra Prodan, Lucas Deimel, Johannes Ahlqvist, Strahil Birov,
Rainer Thiel, Meeri Toivanen, Zoi Kolitsi and Dipak Kalra
49 EU-Funded Telemedicine Projects – Assessment of, and
Lessons Learned From, in the Light of the SARS-CoV-2
Pandemic
Laura Paleari, Virginia Malini, Gabriella Paoli, Stefano Scillieri,
Claudia Bighin, Bernd Blobel and Mauro Giacomini
60 A Review of Artificial Intelligence and Robotics in
Transformed Health Ecosystems
Kerstin Denecke and Claude R. Baudoin
73 Modeling digital health systems to foster interoperability
Frank Oemig and Bernd Blobel
89 Challenges and solutions for transforming health ecosystems
in low- and middle-income countries through artificial
intelligence
Diego M. López, Carolina Rico-Olarte, Bernd Blobel and Carol Hullin
111 Linguistic and ontological challenges of multiple domains
contributing to transformed health ecosystems
Markus Kreuzthaler, Mathias Brochhausen, Cilia Zayas, Bernd Blobel
and Stefan Schulz
126 The ethical challenges of personalized digital health
Els Maeckelberghe, Kinga Zdunek, Sara Marceglia, Bobbie Farsides
and Michael Rigb
Applications
Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications
Технология комплексной поддержки жизненного цикла семантически совместимых интеллектуальных компьютерных систем нового поколения
В издании представлено описание текущей версии открытой технологии онтологического проектирования, производства и эксплуатации семантически совместимых гибридных интеллектуальных компьютерных систем (Технологии OSTIS). Предложена стандартизация интеллектуальных компьютерных систем, а также стандартизация методов и
средств их проектирования, что является важнейшим фактором, обеспечивающим семантическую совместимость интеллектуальных компьютерных систем и их компонентов, что
существенное снижение трудоемкости разработки таких систем.
Книга предназначена всем, кто интересуется проблемами искусственного интеллекта, а также специалистам в области интеллектуальных компьютерных систем и инженерии знаний. Может быть использована студентами, магистрантами и аспирантами специальности «Искусственный интеллект».
Табл. 8. Ил. 223. Библиогр.: 665 назв
WiFi-Based Human Activity Recognition Using Attention-Based BiLSTM
Recently, significant efforts have been made to explore human activity recognition (HAR) techniques that use information gathered by existing indoor wireless infrastructures through WiFi signals without demanding the monitored subject to carry a dedicated device. The key intuition is that different activities introduce different multi-paths in WiFi signals and generate different patterns in the time series of channel state information (CSI). In this paper, we propose and evaluate a full pipeline for a CSI-based human activity recognition framework for 12 activities in three different spatial environments using two deep learning models: ABiLSTM and CNN-ABiLSTM. Evaluation experiments have demonstrated that the proposed models outperform state-of-the-art models. Also, the experiments show that the proposed models can be applied to other environments with different configurations, albeit with some caveats. The proposed ABiLSTM model achieves an overall accuracy of 94.03%, 91.96%, and 92.59% across the 3 target environments. While the proposed CNN-ABiLSTM model reaches an accuracy of 98.54%, 94.25% and 95.09% across those same environments
Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico
Conference proceedings info:
ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies
Raleigh, HI, United States, March 24-26, 2023
Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center
of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático.
de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-
Research Paper: Process Mining and Synthetic Health Data: Reflections and Lessons Learnt
Analysing the treatment pathways in real-world health data can provide valuable insight for clinicians and decision-makers. However, the procedures for acquiring real-world data for research can be restrictive, time-consuming and risks disclosing identifiable information. Synthetic data might enable representative analysis without direct access to sensitive data. In the first part of our paper, we propose an approach for grading synthetic data for process analysis based on its fidelity to relationships found in real-world data. In the second part, we apply our grading approach by assessing cancer patient pathways in a synthetic healthcare dataset (The Simulacrum provided by the English National Cancer Registration and Analysis Service) using process mining. Visualisations of the patient pathways within the synthetic data appear plausible, showing relationships between events confirmed in the underlying non-synthetic data. Data quality issues are also present within the synthetic data which reflect real-world problems and artefacts from the synthetic dataset’s creation. Process mining of synthetic data in healthcare is an emerging field with novel challenges. We conclude that researchers should be aware of the risks when extrapolating results produced from research on synthetic data to real-world scenarios and assess findings with analysts who are able to view the underlying data
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