54 research outputs found

    Managing healthcare transformation towards P5 medicine (Published in Frontiers in Medicine)

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    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 Knowledge Graph Framework for Dementia Research Data

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    Dementia disease research encompasses diverse data modalities, including advanced imaging, deep phenotyping, and multi-omics analysis. However, integrating these disparate data sources has historically posed a significant challenge, obstructing the unification and comprehensive analysis of collected information. In recent years, knowledge graphs have emerged as a powerful tool to address such integration issues by enabling the consolidation of heterogeneous data sources into a structured, interconnected network of knowledge. In this context, we introduce DemKG, an open-source framework designed to facilitate the construction of a knowledge graph integrating dementia research data, comprising three core components: a KG-builder that integrates diverse domain ontologies and data annotations, an extensions ontology providing necessary terms tailored for dementia research, and a versatile transformation module for incorporating study data. In contrast with other current solutions, our framework provides a stable foundation by leveraging established ontologies and community standards and simplifies study data integration while delivering solid ontology design patterns, broadening its usability. Furthermore, the modular approach of its components enhances flexibility and scalability. We showcase how DemKG might aid and improve multi-modal data investigations through a series of proof-of-concept scenarios focused on relevant Alzheimer’s disease biomarkers

    Investigations into the patient voice: a multi-perspective analysis of inflammation

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    The patient is the expert of their medical journey and their experiences go largely unheard in clinical practice. Understanding the patient is important as bridging gaps in the medical domain enhances clinical knowledge, benefiting patient care in addition to improving quality of life. Valuable solutions to these problems lie at the intersection of Machine learning and sentiment analysis; through ontologies, semantic similarity, and clustering. In this thesis, I present challenges and solutions that explore patient quality of life pertaining to two inflammatory diseases: Uveitis and Inflammatory Bowel Disease, which are immune-mediated inflammatory diseases and often undifferentiated. This thesis explores how a patient’s condition and inflammation influences their voice and quality of life via sentiment analysis, clustering, and semantic characterisations. Methods With guidance from domain experts and a foundation derived from clinical consensus documents, I created an application ontology, Ocular Immune-Mediated Inflammatory Diseases Ontology (OcIMIDo), which was enhanced with patient-preferred terms curated from online forum conversations, using a semi-automated statistical approach - with application of annotating term-frequency and sentiment analysis. Semantic similarity was explored using a preexisting embedding model derived from clinical letters to train other models consisting of patient-generated texts for systematic comparison of the clinician and patient voice. In a final experimental chapter, blood markers were clustered and analysed with their corresponding quantitative quality of life outcomes using patients in the UK Biobank with Inflammatory Bowel Disease. Results OcIMIDo is the first of its kind in ophthalmology and sentiment analysis revealed that first posts were more negative compared to replies. Systematic comparisons of embedding models revealed frequent misspellings from clinicians; use of abbreviations from patients; and patient priorities - models performed better when the clinical domain was extended with equivalent-sized, patient-generated data. Clusters unveiled insight into the presence of inflammatory stress and the relationship with happiness and the presence of a maternal smoking history with a Crohn’s disease diagnosis. Summary Patient-preferred terms prove the patient voice provides meaningful text mining and fruitful sentiment analysis, revealing the role a forum plays on patients; semantic similarity highlighted potential novel disease associations and the patient lexicon; and clustering blood markers featured clusters presenting a relationship with sentiment. In summary, this deeper knowledge of quality of life biomarkers through the patient voice can benefit the clinical domain and patient outcomes as understanding the patient can improve the clinical-patient relationship and communication standards: all benefiting the diagnosis process, developing treatment plans, and shortening these intensive time hauls in clinical practice

    Co-design of human-centered, explainable AI for clinical decision support

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    eXplainable AI (XAI) involves two intertwined but separate challenges: the development of techniques to extract explanations from black-box AI models, and the way such explanations are presented to users, i.e., the explanation user interface. Despite its importance, the second aspect has received limited attention so far in the literature. Effective AI explanation interfaces are fundamental for allowing human decision-makers to take advantage and oversee high-risk AI systems effectively. Following an iterative design approach, we present the first cycle of prototyping-testing-redesigning of an explainable AI technique, and its explanation user interface for clinical Decision Support Systems (DSS). We first present an XAI technique that meets the technical requirements of the healthcare domain: sequential, ontology-linked patient data, and multi-label classification tasks. We demonstrate its applicability to explain a clinical DSS, and we design a first prototype of an explanation user interface. Next, we test such a prototype with healthcare providers and collect their feedback, with a two-fold outcome: first, we obtain evidence that explanations increase users’ trust in the XAI system, and second, we obtain useful insights on the perceived deficiencies of their interaction with the system, so that we can re-design a better, more human-centered explanation interface

    Pharmacogenomics of sickle cell disease therapeutics: pain and drug metabolism associated gene variants and hydroxyurea-induced post-transcriptional expression of miRNAs

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    Sickle cell disease (SCD) is a common blood disease caused by a single nucleotide substitution (c.20T>A, p.Glu6Val) in the beta globin gene on chromosome 11. The prevalence of the disease is high throughout large areas in sub-Saharan Africa, the Mediterranean basin, the Middle East, and India due to the level of protection that the sickle cell trait, provides against severe malaria. Approximately 300,000 infants are born per year with sickle cell anemia, which is defined as homozygosity for the sickle hemoglobin (HbS). The majority (nearly 75%) of these births occur in sub-Saharan Africa, particularly in two countries: Nigeria, and the Democratic Republic of the Congo where there are poorly resourced healthcare systems. Early diagnosis, penicillin prophylaxis, blood transfusions, hydroxyurea, and hematopoietic stem-cell transplantation can dramatically improve survival and quality of life for patients with SCD. However, our understanding of the role of genetic and clinical factors in explaining the complex phenotypic diversity of this disease is still limited. Early prediction of the severity, and patients' responses to specific therapeutics of SCD could lead to more precise treatment and management. Beyond well-known modifiers of disease severity, such as fetal hemoglobin (HbF) levels and αthalassemia, other genetic variants might influence specific sub-phenotypes. New treatments and management strategies accounting for these genetic and nongenetic factors could substantially and rapidly improve the quality of life and reduce health care costs for patients with SCD. Patients with SCD are subjected to long term administration of drugs and there is a limited data on pharmacogenomics of SCD therapeutics. Vaso-occlusive crisis (VOC) are the main clinical events of SCD and are associated with recurrent and long-term use of antalgics/opioids and HU. This project aimed to investigate the clinical and genetic predictors of painful vaso-occlusive crisis (VOC) among SCD Cameroon patients by exploring pharmacokinetic determinants of treatment responses as well as post-transcriptional signatures triggered by hydroxyurea treatment, particularly, miRNA expression. SCD patients were recruited from Yaounde Central Hospital and Laquintinie Hospital in Douala (Wonkam et al., 2018, Mnika et al., 2019 (b)), and recent migrants SCD patients from the DRC, recruited at the Haematology Clinic, Groote Schuur Hospital in Cape Town, South Africa (Mnika et al., 2019 (a) and Mnika et al., 2019 (b)). Sociodemographic and clinical data were collected by means of a structured questionnaire. Patients' medical records were reviewed to extract their clinical features over the past 3 years. Specifically, the occurrences of VOC, hematological parameters, hospital outpatient visits, hospitalisation, overt strokes, blood transfusions, and administration of hydroxyurea were recorded. Height, weight, body mass index (BMI), systolic and diastolic blood pressures (SBP and DBP) were measured. Detailed descriptions of patients and sampling methods used in the Cameroonian patients have been reported previously (Wonkam et al., 2018 Mnika et al., 2019 (a) and Mnika et al., 2019 (b)). For the purpose of comparing frequencies of variants, ethnically matched Cameroonian controls were randomly recruited from apparently healthy blood donors in Yaounde for participation in the study. All blood samples were collected for genomic characterisation and analysis. DNA was extracted from peripheral blood, following instructions on the available commercial kit [QIAamp DNA Blood Maxi Kit ® (Qiagen, United States)]. Genotyping (TaqMan and MassArray) was performed for 40 variants in 17 pain-related genes, three fetal haemoglobin (HbF)-promoting loci, two kidney dysfunction-related genes, and HBA1/HBA2 genes for 436 patients. A subset of these samples was also genotyped to analyse 32 core and 267 extended pharmacogenes using commercially available PharmacoScan® platform for characterisation of pharmacokinetic determinant of response. We also compared the pharmacogenes variants from these African groups, to data extracted from the 1000 genomes Project. Moreover, association studies were carried out on pharmacogenes variants with SCD clinical variability. Additionally, protein-protein interaction (PPI) network and enriched biological processes and pathways were investigated. For association studies, statistical models using regression frameworks to analyse 40 variants were performed in R®. For miRNA expression, total RNA was isolated using the miRNeasy kit according to protocol of the Manufacturer (QIAGEN, Hilden, Germany); and sequenced by the Genomic and RNA Profiling Core at Baylor College of Medicine, United States, using the NanoString Platform (NanoString Technologies, Inc., Seattle, WA, United States), according to manufacturer's instructions. Genes with statistically significant changes in expression were analysed using the significance analyses of microarrays (SAM) tools. Female sex, body mass index, Hb/HbF, blood transfusions, leucocytosis and consultation or hospitalisation rates significantly correlated with VOC. Three painrelated gene variants correlated with VOC (CACNA2D3-rs6777055, P = 0·025; DRD2- rs4274224, P = 0·037; KCNS1-rs734784, P= 0·01). Five pain-related gene variants correlated with hospitalization/consultation rates (COMT-rs6269, P = 0·027; FAAHrs4141964, P = 0·003; OPRM1- rs1799971, P = 0·031; ADRB2-rs1042713; P < 0·001; UGT2B7-rs7438135, P = 0·037). The 3·7 kb HBA1/HBA2 deletion correlated with increased VOC (P = 0·002). HbF-promoting loci variants correlated with decreased hospitalisation (BCL11A-rs4671393, P = 0·026; HBS1L-MYB-rs28384513, P = 0·01). APOL1 G1/G2 correlated with increased hospitalisation (P = 0·048). A commercial genotyping array platform (PharmacoScan®) with 4627 markers located in 1191 genes was used to investigate 299 pharmacogenes (32 ADME core and 267 extended pharmacogenes). Based on the PharmacoScan analyses, no statistically significant differences in allele frequencies were detected between SCD cases and controls from Cameroon. A principal component analysis (PCA) revealed that Cameroonians' data clustered with other Africans, but this population is significantly distinct from American, European and Asian populations data. Variant allele frequencies in 21/32 core pharmacogenes were significantly different between the two SCD groups (Cameroon vs. Congo). No correlation between clinical variability and variants in the core genes was detected for both populations under study. An association study of the core and extended PharmacoScan variants to VOC identified statistically significant associations between two single nucleotide polymorphisms (SNPs) to VOC after correction of multiple testing. These two SNPs mapped to 50 genes, with two SNPs located in core pharmacogenes (SLCO4A1- rs118042746, p=1.21e-07; UGT1A10, UGT1A8- rs10176426, p=1.22e-07). Functional enrichment analyses revealed that these 50 genes are involved in three biological processes and four pathways relevant to SCD pathophysiology, including xenobiotic glucuronidation (GO:0052697, p = 2.3e-03), and drug metabolism - other enzymes (p = 2.1e-02). Further analyses of the 50 genes, identified key genes in human proteinprotein networks: NTSR1, LRMDA, SMAD SMAD4 and CDH2. These four genes also interacted with three core pharmacogenes associated with VOC: UGT1A8, UGT1A10 and SLCO4A1. We found 22/798 miRNAs to be differentially expressed under HU treatment, with the majority (13/22) being functionally associated with HbF-regulatory genes, including BCL11A (miR-148b-3p, miR-32-5p, miR-340-5p, miR-29c-3p), MYB (miR-105-5p), KLF-3 (miR-106b-5), and SP1 (miR-29b-3p, miR-625-5p, miR-324-5p, miR-125a-5p, miR-99b-5p, miR-374b-5p, miR-145-5p). The present thesis started by highlighting the scarcity of studies investigating variable responses to pain in SCD patients and then proceeded to addressing this research gap. To our knowledge this is the first body of from Africa to provide evidence supporting the possible development of a genetic risk model for pain in SCD. This is also the first body of work to report an association between these two SNPs and VOC in core and extended pharmacogenes. Our data reveals that the commercial pharmacogenes arrays investigated might need additional evidence for appropriateness among Africans. Therefore, it advocates the need to invest in research exploring population-specific arrays, drug design, targeting, and efficacy, for improved clinical management of patients of African descent. Previous studies have investigated various mechanisms to understand the genomic variations affecting responses to HU, but full understanding of the variable HU-mediated HbF production among individuals affected by SCD remains elusive. The present study showed that mechanisms of HbF production in response to HU, could particularly be mediated through miRNA regulation. The data reveals some alternative perspectives and routes towards identifying new therapeutic targets and approaches for SCD. However, this study needs to be replicated in larger samples in multiple African populations

    Efficient Decision Support Systems

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    This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

    Друга міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні питання (ICSF 2021). Кривий Ріг, Україна, 19-21 травня 2021 року

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    Second International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters (ICSF 2021). Kryvyi Rih, Ukraine, May 19-21, 2021.Друга міжнародна конференція зі сталого майбутнього: екологічні, технологічні, соціальні та економічні питання (ICSF 2021). Кривий Ріг, Україна, 19-21 травня 2021 року

    Neolithic land-use in the Dutch wetlands: estimating the land-use implications of resource exploitation strategies in the Middle Swifterbant Culture (4600-3900 BCE)

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    The Dutch wetlands witness the gradual adoption of Neolithic novelties by foraging societies during the Swifterbant period. Recent analyses provide new insights into the subsistence palette of Middle Swifterbant societies. Small-scale livestock herding and cultivation are in evidence at this time, but their importance if unclear. Within the framework of PAGES Land-use at 6000BP project, we aim to translate the information on resource exploitation into information on land-use that can be incorporated into global climate modelling efforts, with attention for the importance of agriculture. A reconstruction of patterns of resource exploitation and their land-use dimensions is complicated by methodological issues in comparing the results of varied recent investigations. Analyses of organic residues in ceramics have attested to the cooking of aquatic foods, ruminant meat, porcine meat, as well as rare cases of dairy. In terms of vegetative matter, some ceramics exclusively yielded evidence of wild plants, while others preserve cereal remains. Elevated δ15N values of human were interpreted as demonstrating an important aquatic component of the diet well into the 4th millennium BC. Yet recent assays on livestock remains suggest grazing on salt marshes partly accounts for the human values. Finally, renewed archaeozoological investigations have shown the early presence of domestic animals to be more limited than previously thought. We discuss the relative importance of exploited resources to produce a best-fit interpretation of changing patterns of land-use during the Middle Swifterbant phase. Our review combines recent archaeological data with wider data on anthropogenic influence on the landscape. Combining the results of plant macroremains, information from pollen cores about vegetation development, the structure of faunal assemblages, and finds of arable fields and dairy residue, we suggest the most parsimonious interpretation is one of a limited land-use footprint of cultivation and livestock keeping in Dutch wetlands between 4600 and 3900 BCE.NWOVidi 276-60-004Human Origin
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