Representing SNOMED CT Concept Evolutions using Process Profiles

Abstract. SNOMED CT is a very large biomedical terminology supported by a concept-based ontology. In recent years it has been distributed under the new release format 'RF2'. RF2 provides a more consistent and coherent mechanism for keeping track of changes over versions, even to the extent that -in theory at leastany release will contain enough information to allow reconstruction of all previous versions. In this paper, using the January 2016 release of SNOMED CT, we explore various ways to transform change-assertions in RF2 into a more uniform representation with the goal of assessing how faithful these changes are with respect to biomedical reality. Key elements in our approach are (1) recent proposals for the Information Artifact Ontology that provide a realism-based perspective on what it means for a representation to be about something, and (2) the expectation that the theory of what we call 'process profiles' can be applied not merely to quantitative information artifacts but also to other sorts of symbolic representations of processes

Aquisição e Interrogação de Conhecimento de Prática Clínica usando Linguagem Natural

The scientific concepts, methodologies and tools in the Knowledge Representation (KR) sub- domain of applied Artificial Intelligence (AI) came a long way with enormous strides in recent years. The usage of domain conceptualizations that are Ontologies is now powerful enough to aim at computable reasoning over complex realities. One of the most challenging scientific and technical human endeavors is the daily Clinical Prac- tice (CP) of Cardiovascular (CV) specialty healthcare providers. Such a complex domain can benefit largely from the possibility of clinical reasoning aids that are now at the edge of being available. We research into a complete end-to-end solid ontological infrastructure for CP knowledge represen- tation as well as the associated processes to automatically acquire knowledge from clinical texts and reason over it

Clinical practice knowledge acquisition and interrogation using natural language: aquisição e interrogação de conhecimento de prática clínica usando linguagem natural

Os conceitos científicos, metodologias e ferramentas no sub-dominio da Representação de Conhecimento da área da Inteligência Artificial Aplicada têm sofrido avanços muito significativos nos anos recentes. A utilização de Ontologias como conceptualizações de domínios é agora suficientemente poderosa para aspirar ao raciocínio computacional sobre realidades complexas. Uma das tarefas científica e tecnicamente mais desafiante é prestação de cuidados pelos profissionais de saúde na especialidade cardiovascular. Um domínio de tal forma complexo pode beneficiar largamente da possibilidade de ajudas ao raciocínio clínico que estão neste momento a beira de ficarem disponíveis. Investigamos no sentido de desenvolver uma infraestrutura sólida e completa para a representação de conhecimento na prática clínica bem como os processes associados para adquirir o conhecimento a partir de textos clínicos e raciocinar automaticamente sobre esse conhecimento; ABSTRACT: The scientific concepts, methodologies and tools in the Knowledge Representation (KR) subdomain of applied Artificial Intelligence (AI) came a long way with enormous strides in recent years. The usage of domain conceptualizations that are Ontologies is now powerful enough to aim at computable reasoning over complex realities. One of the most challenging scientific and technical human endeavors is the daily Clinical Practice (CP) of Cardiovascular (C V) specialty healthcare providers. Such a complex domain can benefit largely from the possibility of clinical reasoning aids that are now at the edge of being available. We research into al complete end-to-end solid ontological infrastructure for CP knowledge representation as well as the associated processes to automatically acquire knowledge from clinical texts and reason over it

Towards a system of concepts for Family Medicine. Multilingual indexing in General Practice/ Family Medicine in the era of Semantic Web

UNIVERSITY OF LIÈGE, BELGIUM Executive Summary Faculty of Medicine Département Universitaire de Médecine Générale. Unité de recherche Soins Primaires et Santé Doctor in biomedical sciences Towards a system of concepts for Family Medicine. Multilingual indexing in General Practice/ Family Medicine in the era of SemanticWeb by Dr. Marc JAMOULLE Introduction This thesis is about giving visibility to the often overlooked work of family physicians and consequently, is about grey literature in General Practice and Family Medicine (GP/FM). It often seems that conference organizers do not think of GP/FM as a knowledge-producing discipline that deserves active dissemination. A conference is organized, but not much is done with the knowledge shared at these meetings. In turn, the knowledge cannot be reused or reapplied. This these is also about indexing. To find knowledge back, indexing is mandatory. We must prepare tools that will automatically index the thousands of abstracts that family doctors produce each year in various languages. And finally this work is about semantics1. It is an introduction to health terminologies, ontologies, semantic data, and linked open data. All are expressions of the next step: Semantic Web for health care data. Concepts, units of thought expressed by terms, will be our target and must have the ability to be expressed in multiple languages. In turn, three areas of knowledge are at stake in this study: (i) Family Medicine as a pillar of primary health care, (ii) computational linguistics, and (iii) health information systems. Aim • To identify knowledge produced by General practitioners (GPs) by improving annotation of grey literature in Primary Health Care • To propose an experimental indexing system, acting as draft for a standardized table of content of GP/GM • To improve the searchability of repositories for grey literature in GP/GM. 1For specific terms, see the Glossary page 257 x Methods The first step aimed to design the taxonomy by identifying relevant concepts in a compiled corpus of GP/FM texts. We have studied the concepts identified in nearly two thousand communications of GPs during conferences. The relevant concepts belong to the fields that are focusing on GP/FM activities (e.g. teaching, ethics, management or environmental hazard issues). The second step was the development of an on-line, multilingual, terminological resource for each category of the resulting taxonomy, named Q-Codes. We have designed this terminology in the form of a lightweight ontology, accessible on-line for readers and ready for use by computers of the semantic web. It is also fit for the Linked Open Data universe. Results We propose 182 Q-Codes in an on-line multilingual database (10 languages) (www.hetop.eu/Q) acting each as a filter for Medline. Q-Codes are also available under the form of Unique Resource Identifiers (URIs) and are exportable in Web Ontology Language (OWL). The International Classification of Primary Care (ICPC) is linked to Q-Codes in order to form the Core Content Classification in General Practice/Family Medicine (3CGP). So far, 3CGP is in use by humans in pedagogy, in bibliographic studies, in indexing congresses, master theses and other forms of grey literature in GP/FM. Use by computers is experimented in automatic classifiers, annotators and natural language processing. Discussion To the best of our knowledge, this is the first attempt to expand the ICPC coding system with an extension for family physician contextual issues, thus covering non-clinical content of practice. It remains to be proven that our proposed terminology will help in dealing with more complex systems, such as MeSH, to support information storage and retrieval activities. However, this exercise is proposed as a first step in the creation of an ontology of GP/FM and as an opening to the complex world of Semantic Web technologies. Conclusion We expect that the creation of this terminological resource for indexing abstracts and for facilitating Medline searches for general practitioners, researchers and students in medicine will reduce loss of knowledge in the domain of GP/FM. In addition, through better indexing of the grey literature (congress abstracts, master’s and doctoral theses), we hope to enhance the accessibility of research results and give visibility to the invisible work of family physicians

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

A framework for analyzing changes in health care lexicons and nomenclatures

Ontologies play a crucial role in current web-based biomedical applications for capturing contextual knowledge in the domain of life sciences. Many of the so-called bio-ontologies and controlled vocabularies are known to be seriously defective from both terminological and ontological perspectives, and do not sufficiently comply with the standards to be considered formai ontologies. Therefore, they are continuously evolving in order to fix the problems and provide valid knowledge. Moreover, many problems in ontology evolution often originate from incomplete knowledge about the given domain. As our knowledge improves, the related definitions in the ontologies will be altered. This problem is inadequately addressed by available tools and algorithms, mostly due to the lack of suitable knowledge representation formalisms to deal with temporal abstract notations, and the overreliance on human factors. Also most of the current approaches have been focused on changes within the internal structure of ontologies, and interactions with other existing ontologies have been widely neglected. In this research, alter revealing and classifying some of the common alterations in a number of popular biomedical ontologies, we present a novel agent-based framework, RLR (Represent, Legitimate, and Reproduce), to semi-automatically manage the evolution of bio-ontologies, with emphasis on the FungalWeb Ontology, with minimal human intervention. RLR assists and guides ontology engineers through the change management process in general, and aids in tracking and representing the changes, particularly through the use of category theory. Category theory has been used as a mathematical vehicle for modeling changes in ontologies and representing agents' interactions, independent of any specific choice of ontology language or particular implementation. We have also employed rule-based hierarchical graph transformation techniques to propose a more specific semantics for analyzing ontological changes and transformations between different versions of an ontology, as well as tracking the effects of a change in different levels of abstractions. Thus, the RLR framework enables one to manage changes in ontologies, not as standalone artifacts in isolation, but in contact with other ontologies in an openly distributed semantic web environment. The emphasis upon the generality and abstractness makes RLR more feasible in the multi-disciplinary domain of biomedical Ontology change management

pHealth 2021. Proc. of the 18th Internat. Conf. on Wearable Micro and Nano Technologies for Personalised Health, 8-10 November 2021, Genoa, Italy

Smart mobile systems – microsystems, smart textiles, smart implants, sensor-controlled medical devices – together with related body, local and wide-area networks up to cloud services, have become important enablers for telemedicine and the next generation of healthcare services. The multilateral benefits of pHealth technologies offer enormous potential for all stakeholder communities, not only in terms of improvements in medical quality and industrial competitiveness, but also for the management of healthcare costs and, last but not least, the improvement of patient experience. This book presents the proceedings of pHealth 2021, the 18th in a series of conferences on wearable micro and nano technologies for personalized health with personal health management systems, hosted by the University of Genoa, Italy, and held as an online event from 8 – 10 November 2021. The conference focused on digital health ecosystems in the transformation of healthcare towards personalized, participative, preventive, predictive precision medicine (5P medicine). The book contains 46 peer-reviewed papers (1 keynote, 5 invited papers, 33 full papers, and 7 poster papers). Subjects covered include the deployment of mobile technologies, micro-nano-bio smart systems, bio-data management and analytics, autonomous and intelligent systems, the Health Internet of Things (HIoT), as well as potential risks for security and privacy, and the motivation and empowerment of patients in care processes. Providing an overview of current advances in personalized health and health management, the book will be of interest to all those working in the field of healthcare today

Use of Decision Tables to Model Assistance Knowledge to Train Medical Residents

En aquesta tesi es presenta un model de coneixement clínic basat en taules de decisió que permet representar les fases de diagnòstic, tractament i pronòstic de diferents malalties. Les taules de decisió que s'obtenen per a cada fase del model han estat utilitzades per representar malalties reals a partir de guies de pràctica clínica. En el cas del diagnòstic s'han representat les vuit causes secundàries més comuns de la hipertensió arterial. En el cas del tractament i pronòstic s'han representat set diferents xocs en emergències. Les taules de decisió que hem obtingut per a cadascuna de les malalties s'han utilitzat com a base per crear dues eines d'entrenament mèdic, dirigides a residents. Totes dues eines s'han provat a l'Hospital Clínic de Barcelona amb diferents grups de residents. Després de les proves s'ha conclòs que les taules de decisió són adequades per a la representació del coneixement mèdic en totes tres fases. A més, les eines d'aprenentatge han estat efectives a l'hora d'ensenyar els procediments mèdics, especialment als residents amb menys experiència prèvia.En esta tesis se presenta un modelo de conocimiento clínico basado en tablas de decisión que permite representar las fases de diagnostico, tratamiento y pronostico de distintas enfermedades. Las tablas de decisión que se obtienen para cada fase del modelo han sido utilizadas para representar enfermedades reales a partir de guías de práctica clínica. En el caso del diagnóstico se han representado las ocho causas secundarias más comunes de la hipertensión arterial. En el caso del tratamiento y pronóstico se han representado siete diferentes shocks en emergencias. Las tablas de decisión que hemos obtenido para cada una de las enfermedades se han usado como base para crear dos herramientas de entrenamiento médico, dirigido a residentes. Ambas herramientas se han probado en el Hospital Clínic de Barcelona con distintos grupos de residentes. Tras las pruebas se ha concluido que las tablas de decisión son adecuadas para la representación del conocimiento medico en las tres fases. Además, las herramientas de aprendizaje han sido efectivas a la hora de enseñar los procedimientos médicos, en especial a los residentes con menos experiencia previa.In this thesis a clinical knowledge model based on decision tables is presented. This model allows us to represent the stages of diagnosis, treatment, and prognosis of different diseases. The decision tables obtained for each phase of the model have been used to represent real diseases from clinical practice guidelines. In the case of diagnosis, we represented eight of the most common secondary causes of hypertension. For the treatment and prognosis we represented seven different emergency shocks. The decision tables obtained for each disease have been used as the basis for two medical training tools aimed to residents. Both tools have been tested in the Hospital Clínic de Barcelona with different groups of residents. After testing, it was concluded that decision tables are suitable for the representation of medical knowledge in all three phases. In addition, the learning tools have been effective in teaching medical procedures, especially for untrained residents