Deliverables
Describes the final outcomes of the project based on the corresponding Management Report on M36 but will be distributed to public.
Health in All Policy Making Utilizing Big Data v1. Merge Deliverables: D5.11+D5.13
This series of deliverables will describe the dissemination and collaboration strategy and the activities followed during the reporting periods as well as the results from these activities (see Section 2.2.3 for a detailed description of the planned dissemination strategy for CrowdHEALTH). In particular, a report on TMU activities at International level will be included.
This document will outline the design of the scenarios, including a description of them, the scenario requirements, the infrastructures and platforms that will be utilized and the use of CrowdHEALTH technologies.
This document will outline the design of the scenarios, including a description of them, the scenario requirements, the infrastructures and platforms that will be utilized and the use of CrowdHEALTH technologies.
This report will identify the key components of CrowdHEALTH and define the interfaces and interactions between them. An internal report will be developed in M3 and will serve as a basis to kick-off the research activities of the project (planned to start in M4).
Data Visualization Framework: Design and Prototype Merge Deliverables: D4.13 + D4.14 + D4.15 + D4.16
Reliable Information Provision in Healthcare: Final Design and Prototype Merge deliverables: D3.20 + D3.22
Advanced Interoperability Techniques: Final Design and Prototype Merge deliverables: D3.10 + D3.11 + D3.13 + D3.14
This report will provide a roadmap for adoption and exploitation of CrowdHEALTH outcomes by different stakeholders in multidisciplinary cases. The roadmap will highlight current concerns and limitations in the healthcare ecosystem and means to overcome them.
This report will examine the SotA for the technologies involved in CrowdHEALTH, present possible future trends and analyse the identified both use case and technical requirements. In M3 an internal deliverable will be provided in order to provide input to the initial conceptual model and architecture. During the course of the project the technologies and requirements related to CrowdHEALTH will continue being investigated in order to ensure that the objectives and innovations of the project are valid, work is performed taking into account the latest SotA and developments fulfil the identified goals and requirements.
This deliverable will focus on the publication of the initial set of materials that will define and promote project’s identity. It will include the creation of a project logo, a project factsheet, an MS PowerPoint presentation providing a general description of CrowdHEALTH, project’s official web site and templates for the official documents to be developed within the project.
Clinical Pathways Mining: Design and Prototype Merge Deliverables: D5.7+D5.8+D5.9+D5.10
The deliverable D5.1 will describe the models and the methodologies for the evaluation of public health policies.
This document will outline the architecture and design of the description framework and the specification of the envisioned abstracted API for all information sources.
This series of deliverables will describe the dissemination and collaboration strategy and the activities followed during the reporting periods as well as the results from these activities (see Section 2.2.3 for a detailed description of the planned dissemination strategy for CrowdHEALTH). An internal plan will be developed in M6 to drive the initial dissemination activities of the project.
Data-driven Analytics for Risk Stratification: Design and Prototype Merge Deliverables: D5.4 + D5.5 + D5.6
Modelling and Evaluation of Policies
This report will identify the key components of CrowdHEALTH and define the interfaces and interactions between them. An internal report will be developed in M3 and will serve as a basis to kick-off the research activities of the project (planned to start in M4).
This report will detail all engagement with standardisation bodies or similar fora and the corresponding potential contributions (see Section 2.2.2.4 for a detailed description of the planned standardisation strategy for CrowdHEALTH).
HHRs Networks Formulation: Design and Prototype Merge deliverables: D3.15 + D3.16 + D3.17 + D3.18
This document will outline the information model and describe the mechanisms investigated and developed in to provide reliable information from data sources. The deliverable will provide the relevant specification as well as descriptions of the mechanisms to overcome the intrinsic information volatility in the healthcare ecosystem.
Health in All Policy Making Utilizing Big Data v2 Merge Deliverables: D5.12 + D5.14
This document will provide detailed specifications for the interoperability techniques and mechanisms.
Multimodal Forecasting and Casual Techniques: Final Design and Prototype Merge Deliverables: D5.16 + D5.17 + D5.19 + D5.20
Integrated Holistic Security and Privacy Framework: Final Design and Prototype Merge Deliverables: D4.18 + D4.19 + D4.21 + D4.22
This report will consolidate the results from the work performed in order to provide the integrated view of CrowdHEALTH outcomes.
This report will detail all engagement with standardisation bodies or similar fora and the corresponding potential contributions (see Section 2.2.2.4 for a detailed description of the planned standardisation strategy for CrowdHEALTH).
These reports will include the outcomes of the evaluation (in terms of consistency, correctness, completeness) for the CrowdHEALTH technologies and the benefits they provide in different cases, as well as recommendations to the research activities of the project following the evaluation process. The intermediate versions will feed back to the architecture specification while the final version will act as a “Best practices and Lessons Learned” report.
This document will outline the design of the scenarios, including a description of them, the scenario requirements, the infrastructures and platforms that will be utilized and the use of CrowdHEALTH technologies.
This document will provide a detailed architecture of the holistic security and privacy framework including the trust management, data anonymization, access control and authorization mechanisms.
Data Sources and Gateways: Final Design and Prototype Merge deliverables: D3.6 + D3.8
This report will examine the SotA for the technologies involved in CrowdHEALTH, present possible future trends and analyse the identified both use case and technical requirements. In M3 an internal deliverable will be provided in order to provide input to the initial conceptual model and architecture. During the course of the project the technologies and requirements related to CrowdHEALTH will continue being investigated in order to ensure that the objectives and innovations of the project are valid, work is performed taking into account the latest SotA and developments fulfil the identified goals and requirements.
Generating and Analyzing Knowledge Framework: Final Design and Prototype Merge deliverables: D4.8 + D4.9 + D4.11 + D4.12
This series of deliverables will describe the dissemination and collaboration strategy and the activities followed during the reporting periods as well as the results from these activities (see Section 2.2.3 for a detailed description of the planned dissemination strategy for CrowdHEALTH). In particular, a report on TMU activities at International level will be included.
This document will provide detailed specifications for the mechanisms and models that generate contextual knowledge in healthcare.
This report will examine the SotA for the technologies involved in CrowdHEALTH, present possible future trends and analyse the identified both use case and technical requirements. In M3 an internal deliverable will be provided in order to provide input to the initial conceptual model and architecture. During the course of the project the technologies and requirements related to CrowdHEALTH will continue being investigated in order to ensure that the objectives and innovations of the project are valid, work is performed taking into account the latest SotA and developments fulfil the identified goals and requirements.
This document will outline the health records properties that will extend current structures with holistic health attributes as well with social attributes regarding their behavioural, interaction and operation patterns within a network of HHRs.
This deliverable describes the forecasting, simulation and causal mechanisms analysis functionality of the policies development toolkit.
This deliverable will provide the processes and techniques for the risk assessment and stratification.
These reports will include the outcomes of the evaluation (in terms of consistency, correctness, completeness) for the CrowdHEALTH technologies and the benefits they provide in different cases, as well as recommendations to the research activities of the project following the evaluation process. The intermediate versions will feed back to the architecture specification while the final version will act as a “Best practices and Lessons Learned” report. This report will also include Evaluation Outcome of Chronic Kidney Disease Use Case from TMU.
Health Record Structure: Final Design and Prototype Merge deliverables: D3.2 + D3.4
These reports will include the outcomes of the evaluation (in terms of consistency, correctness, completeness) for the CrowdHEALTH technologies and the benefits they provide in different cases, as well as recommendations to the research activities of the project following the evaluation process. The intermediate versions will feed back to the architecture specification while the final version will act as a “Best practices and Lessons Learned” report.
This report will identify the key components of CrowdHEALTH and define the interfaces and interactions between them. An internal report will be developed in M3 and will serve as a basis to kick-off the research activities of the project (planned to start in M4).
This prototype will implement the mechanisms specified in D3.5.
Policiy Development Toolkit Merge Deliverables: D5.21 + D5.22
This prototype will deliver the software implementations of the gateways framework and the unified APIs.
These prototypes will deliver the envisioned integrated holistic security and privacy framework.
Is the software prototype for the above deliverables D5.15/D5.16/D5.17.
Is the software prototype for deliverable D5.23. The App will be uploaded to Google Play.
These prototypes will deliver the services for the different scenarios and showcase the applicability of the CrowdHEALTH technologies under different applications and contexts.
These prototypes will deliver the mechanisms managing the uncertainty and volatility following the design and specifications in D3.19/D20.
These prototypes will deliver the enriched HHR structures specified in D3.1/D3.2 including mechanisms enabling dynamic patterns exploitation for real-time adaptation.
These prototypes will implement the mechanisms specified in D4.7/D4.8/D4.9.
These prototypes will deliver the services for the different scenarios and showcase the applicability of the CrowdHEALTH technologies under different applications and contexts.
These prototypes will deliver the services for the different scenarios and showcase the applicability of the CrowdHEALTH technologies under different applications and contexts.
CrowdHEALTH will participate in the Pilot on Open Research Data in H2020 and will endeavour to offer open access to its scientific results reported in publications, to the relevant scientific data and to data generated during the course of the project. The plan will identify the best practices and specific standards for the generated data and assess their suitability for sharing and reuse in accordance with official guidelines (additional information is provided in Section 2.2.4).
Publications
Author(s): Athanasios Kiourtis, Argyro Mavrogiorgou, Dimosthenis Kyriazis
Published in: 2017 10th International Conference on Developments in eSystems Engineering (DeSE), 2017, Page(s) 175-181
DOI: 10.1109/DeSE.2017.9
Author(s): Argyro Mavrogiorgou, Athanasios Kiourtis, Dimosthenis Kyriazis
Published in: Complex, Intelligent, and Software Intensive Systems, 2017, Page(s) 885-895
DOI: 10.1007/978-3-319-61566-0_84
Author(s): Dimosthenis Kyriazis, Serge Autexier, Iván Brondino, Michael Boniface, Lucas Donat, Vegard Engen, Rafael Fernandez, Ricardo Jimenez-Peris, Blanca Jordan, Gregor Jurak, Athanasios Kiourtis, Thanos Kosmidis, Mitja Lustrek, Ilias Maglogiannis, John Mantas, Antonio Martinez, Argyro Mavrogiorgou, Andreas Menychtas, Lydia Montandon, Cosmin-Septimiu Nechifor, Sokratis Nifakos, Alexandra Papageorgiou, Ma
Published in: Informatics Empowers Healthcare Transformation, 2017, Page(s) 19 - 23
DOI: 10.3233/978-1-61499-781-8-19
Author(s): Athanasios Kiourtis, Argyro Mavrogiorgou, Dimosthenis Kyriazis, Marinos Themistocleous
Published in: Information Systems, 2017, Page(s) 324-336
DOI: 10.1007/978-3-319-65930-5_27
Author(s): Argyro Mavrogiorgou, Athanasios Kiourtis, Dimosthenis Kyriazis, Marinos Themistocleous
Published in: Information Systems, 2017, Page(s) 82-96
DOI: 10.1007/978-3-319-65930-5_7
Author(s): Argyro Mavrogiorgou, Athanasios Kiourtis, Dimosthenis Kyriazis
Published in: Economics of Grids, Clouds, Systems, and Services, 2017, Page(s) 67-77
DOI: 10.1007/978-3-319-68066-8_6
Author(s): Athanasios Kiourtis, Argyro Mavrogiorgou, Dimosthenis Kyriazis
Published in: 2017 International Symposium on Computer Science and Intelligent Controls (ISCSIC), 2017, Page(s) 102-107
DOI: 10.1109/ISCSIC.2017.13
Author(s): Athanasios Kiourtis, Argyro Mavrogiorgou, Dimosthenis Kyriazis
Published in: Joint Conference on Knowledge-Based Software Engineering, 2018, Page(s) 178-188
DOI: 10.1007/978-3-319-97679-2_18
Author(s): Athanasios Kiourtis, Argyro Mavrogiorgou, Dimosthenis Kyriazis
Published in: 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom), 2018, Page(s) 1-7
DOI: 10.1109/healthcom.2018.8531149
Author(s): Argyro Mavrogiorgou, Athanasios Kiourtis, Chrysostomos Symvoulidis, Dimosthenis Kyriazis
Published in: 2018 Fifth International Conference on Internet of Things: Systems, Management and Security, 2018, Page(s) 62-69
DOI: 10.1109/iotsms.2018.8554720
Author(s): Konstantinos Moutselos, Dimosthenis Kyriazis, Vasiliki Diamantopoulou, Ilias Maglogiannis
Published in: 2018 IEEE International Conference on Big Data (Big Data), 2018, Page(s) 3774-3779
DOI: 10.1109/bigdata.2018.8622449
Author(s): Lydia Montandon, Dimosthenis Kyriazis, Zoe Valero-Ramon, Carlos Fernandez-Llatas, Vicente Traver
Published in: 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS), 2019, Page(s) 1-3
DOI: 10.1109/cbms.2019.00010
Author(s): Argyro Mavrogiorgou, Athanasios Kiourtis, Marios Touloupou, Dimosthenis Kyriazis
Published in: 2019 Eleventh International Conference on Ubiquitous and Future Networks (ICUFN), 2019, Page(s) 200-205
DOI: 10.1109/icufn.2019.8806153
Author(s): Argyro Mavrogiorgou, Athanasios Kiourtis, Dimosthenis Kyriazis
Published in: 2019 25th Conference of Open Innovations Association (FRUCT), 2019, Page(s) 211-219
DOI: 10.23919/fruct48121.2019.8981527
Author(s): Argyro Mavrogiorgou, Athanasios Kiourtis, Konstantinos Perakis, Stamatios Pitsios, Dimosthenis Kyriazis
Published in: Sensors, Issue 19/9, 2019, Page(s) 1978, ISSN 1424-8220
DOI: 10.3390/s19091978
Author(s): Athanasios Kiourtis, Argyro Mavrogiorgou, Andreas Menychtas, Ilias Maglogiannis, Dimosthenis Kyriazis
Published in: Journal of Medical Systems, Issue 43/3, 2019, ISSN 0148-5598
DOI: 10.1007/s10916-019-1183-y
Author(s): Argyro Mavrogiorgou, Athanasios Kiourtis, Konstantinos Perakis, Dimitrios Miltiadou, Stamatios Pitsios, Dimosthenis Kyriazis
Published in: Computer Methods and Programs in Biomedicine, Issue 181, 2019, Page(s) 104967, ISSN 0169-2607
DOI: 10.1016/j.cmpb.2019.06.026
Author(s): Andriana Magdalinoua, John Mantas, Lydia Montandon, Patrick Weber, Parisis Gallos
Published in: Acta Informatica Medica, Issue 27/5, 2019, Page(s) 348, ISSN 0353-8109
DOI: 10.5455/aim.2019.27.348-354
Author(s): Stefanos Malliaros, Christos Xenakis, George Moldovan, John Mantas, Andriana Magdalinou, Lydia Montandon
Published in: Acta Informatica Medica, Issue 27/5, 2019, Page(s) 333, ISSN 0353-8109
DOI: 10.5455/aim.2019.27.333-340
Author(s): Konstantinos Perakis, Dimitris Miltiadou, Antonio Nigro, Francesco Torelli, Lydia Mantas, Andriana Magdalinou, Argyro Mavrogiorgou, Dimosthenis Kyriazis
Published in: Acta Informatica Medica, Issue 27/5, 2019, Page(s) 341, ISSN 0353-8109
DOI: 10.5455/aim.2019.27.341-347
Author(s): Santiago Lete, Carlos Cavero, Mitja trek, Dimosthenis Kyriazis, Athanasios Kiourtis, Andriana Magdalinou, John Mantas, Lydia Montandon
Published in: Acta Informatica Medica, Issue 27/5, 2019, Page(s) 355, ISSN 0353-8109
DOI: 10.5455/aim.2019.27.355-361
Author(s): Usman Wajid, Chris Orton, Andriana Magdalinou, John Mantas, Lydia Montandon
Published in: Acta Informatica Medica, Issue 27/5, 2019, Page(s) 362, ISSN 0353-8109
DOI: 10.5455/aim.2019.27.362-368
Author(s): Dimosthenis Kyriazis, Serge Autexier, Iv Brondino, Michael Boniface, Lucas Donat, Vegard Engen, Rafael Fernandez, Ricardo Peris, Blanca Jordan, Gregor Jurak, Athanasios Kiourtis, Thanos Kosmidis, Mitja Lustrek, Ilias Maglogiannis, John Mantas, Antonio Martinez, Argyro Mavrogiorgou, Andreas Menychtas, Lydia Montandon, Cosmin Nechifor, Sokratis Nifakos, Alexandra Papageorgiou, Marta Martinez, Manuel
Published in: Acta Informatica Medica, Issue 27/5, 2019, Page(s) 369, ISSN 0353-8109
DOI: 10.5455/aim.2019.27.369-373
Author(s): Santiago Lete, Carlos Cavero, Andriana Magdalinou, John Mantas, Lydia Montandon
Published in: Acta Informatica Medica, Issue 28/1, 2020, Page(s) 52, ISSN 0353-8109
DOI: 10.5455/aim.2020.28.52-57
Author(s): Alice Vassiliou, Christina Georgakopoulou, Alexandra Papageorgiou, Spiros Georgakopoulos, Spiros Goulas, Theodors Paschalis, Panagiotis Paterakis, Parisis Gallos, Dimos Kyriazis, Vassilis Plagianakos
Published in: Acta Informatica Medica, Issue 28/1, 2020, Page(s) 65, ISSN 0353-8109
DOI: 10.5455/aim.2020.28.65-70
Author(s): Konstantinos Moutselos, Ilias Maglogiannis, Dimosthenis Kyriazis, Andrea Granados, Vassilis Plagianakos, Alexandra Papageorgiu, Septimiu Nechifor, John Mantas, Andriana Magdalinou, Lydia Montandon
Published in: Acta Informatica Medica, Issue 28/1, 2020, Page(s) 58, ISSN 0353-8109
DOI: 10.5455/aim.2020.28.58-64
Author(s): John Minou, John Mantas, Flora Malamateniou, Daphne Kaitelidou
Published in: Acta Informatica Medica, Issue 28/1, 2020, Page(s) 48, ISSN 0353-8109
DOI: 10.5455/aim.2020.28.48-51
Author(s): Konstantinos Moutselos, Ilias Maglogiannis
Published in: Medical Archives, Issue 74/1, 2020, Page(s) 47, ISSN 0350-199X
DOI: 10.5455/medarh.2020.74.47-53
Author(s): John Minou, John Mantas, Flora Malamateniou, Daphne Kaitelidou
Published in: Medical Archives, Issue 74/1, 2020, Page(s) 39, ISSN 0350-199X
DOI: 10.5455/medarh.2020.74.39-41
Author(s): Christian Lovis, George Mihalas, John Mantas, Niels Peek, Ran Balicer, Izet Masic, Lacramioara Stoicu-Tivadar
Published in: Yearbook of Medical Informatics, Issue 27/01, 2018, Page(s) 296-301, ISSN 0943-4747
DOI: 10.1055/s-0038-1641209
Author(s): Athanasios Kiourtis, Argyro Mavrogiorgou, Sokratis Nifakos, Dimosthenis Kyriazis
Published in: Intelligent Computing - Proceedings of the 2019 Computing Conference, Volume 1, Issue 997, 2019, Page(s) 956-970
DOI: 10.1007/978-3-030-22871-2_68