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CORDIS - EU research results
CORDIS

Advanced personalised, multi-scale computer models preventing OsteoArthritis

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Training seminars (opens in new window)

The process of technology and knowledge transfer will be supported by the appropriate focused training of partners. This will be achieved through the organization of 2 training seminars. In order to ensure the wide-scale uptake of knowledge and technology generated within the sector, the partners involved will structure dedicated training programs for the internal staff. In addition, the efficient transfer of knowledge and expertise from the RTD partners to the rest of the Consortium will also be planned and executed.

OACTIVE dissemination workshop (opens in new window)

A dedicated workshop will be organised to present the OACTIVE technologies. Representatives will be invited from interested local authorities, key scientists, as well as policy makers within Europe, targeting as many Member States as possible, but also including some representatives from outside Europe. The event will also be open to the interested public.

Computational intelligence models development (opens in new window)

This deliverable will contain a detailed documentation of the machine learning and deep learning infrastructure that will be developed in OACTIVE.

OACTIVE final conference (opens in new window)

A final conference will be organised presenting the main outputs and findings and methodological advances of the project. The event will include thematic breakout sessions, panel discussions, and networking events to build strong partnerships

OACTIVE Web Site and media presence (opens in new window)

This deliverable will include: i) The project website including a public section and a secure section, which will be accessible only by project partners and the Commission; ii) The OACTIVE brochure (including objectives, concept and profiles of partners); iii) Presence on popular social networks.

OACTIVE videos (opens in new window)

Two promotional videos (One teaser and one final) will be produced also. One video will be produced at M3 of the project where the OACTIVE objectives will be described and one at M36 presenting the project’s achievements

Ontology-based framework for data standardisation (opens in new window)

This deliverable presents the employed ontology-based mechanisms for data standardisation

OA in vitro models (opens in new window)

This deliverable will identify the most faithful in vitro model of OA-like changes between trauma-induced OA and inflammatory cytokines signalling. Furthermore, it will validate the use of engineered constructs for in vitro high throughput analysis of OA severity and progression in relation to local cellular responses.

Design and implementation of personalised predictive models (opens in new window)

This deliverable will present the working prototypes of the personalised predictive OACTIVE models used either for prevention, diagnosis or even during the intervention stage.

Analysis of hardware devices and software tools. Game hardware and software design. (opens in new window)

This document will contain the studies made on the different devices, architectures, and software platforms available for the project's game system. It will identify the devices taking part in the OACTIVE game architecture and also the graphics engines to be used for games development.

Effects of hormones during OA (opens in new window)

This deliverable will assess whether cycling hormones have a protective effect against OA and will provide cellular response profiles to the presence/absence of hormones.

First version of Ethics and Safety Manual (opens in new window)

This report will define the first version of ethical and safety management issues.

Evaluation Toolbox Documentation (opens in new window)

This deliverable describes the evaluation rationale, roadmap, methods and processes that will be used for the evaluation and the validation of the OACTIVE system.

Documentation on the qualification of biomarkers found in serum of OA patients (opens in new window)

This deliverable will contain a detailed documentation and qualification of three Prognostic Biomarkers of Bone and Cartilage Degradation and Synthesis and 3 Inflammatory Biomarkers and their concentrations in serum samples from OA patients.

Data Collection protocol (opens in new window)

This report will describe in detail the data collection and evaluation protocol that will be followed in WP6.

Best practices handbook (opens in new window)

A handbook presenting lessons learnt and best practices learnt during the project will be developed and given to public, targeting to the long term contribution on to the formation of common policies on OA treatment in EU level.

Documentation of social attributes and interdependencies of cognitive and social determinants (opens in new window)

This deliverable will contain a detailed documentation of the social attributes and the description of the complex interdependencies and interactions between the different social factor families (social position, social context, psychological influences, personal factors).

Markers and cellular responses in OA osteochondral units (opens in new window)

This deliverable will associate in vitro analysis with in vivo assessments on the basis of matching imaging and biomarkers results. Furthermore, this deliverable will provide a dataset including cartilage and bone soluble markers, microCT imaging of bone and cartilage, cellular response by qRT-PCR, histology and immunohistochemistry that will be used for the generation of the multiscale hypermodel.

Evaluation of OACTIVE in big data registries (opens in new window)

This deliverable describes the results and outcomes of the long term evaluation of OACTIVE using data from big data registries.

User Behaviour Modelling Documentation (opens in new window)

This deliverable will contain a detailed documentation of the datasets and the analyses of the user behaviour based on the sensor outputs from the different services

Documentation of behavioural attributes and interdependencies of physical factors (opens in new window)

This deliverable will contain a detailed documentation of the behavioural attributes and the description of the complex interdependencies and interactions between them.

Data Management Infrastructure (opens in new window)

This report will describe the cloud-based infrastructure that will be setup for the project and its functionalities.

User requirements analysis report (opens in new window)

This deliverable will pro-vide a reference set of user requirements. It should constitute a reference guide for the development of different functions of OACTIVE. One chapter of this report will be dedicated to the analysis of the state-of-the-art technology.

Report on qualification of OA-related exosomal and microbiome biomarkers (opens in new window)

This deliverable will contain a detailed documentation and qualification of exosomal biomarkers isolated from fluid samples of OA patients.

Evaluation of OACTIVE in human population (opens in new window)

This deliverable describes the evaluation results and outcomes of the clinical studies.

Final version of Ethics and Safety Manual (opens in new window)

This report will define the final version of ethical and safety management issues.

Data management plan Strategy (opens in new window)

This deliverable will determine the strategy by which the research data generated by the project will be made open for maximizing their re-use.

OACTIVE personalized computer biomechanical models (opens in new window)

This deliverable will contain a detailed documentation and description of the biomechanical models developed and the associated computer files.

OACTIVE biomechanical simulation and analysis engines (opens in new window)

This deliverable will contain a detailed documentation and description of the biomechanical simulations and outcomes and the associated computer files

Publications

Machine learning in knee osteoarthritis: A review (opens in new window)

Author(s): C.Kokkotis; S.Moustakidis; E.Papageorgiou; G.Giakas; E.Tsaopoulos
Published in: Osteoarthritis and Cartilage Open, 2020, ISSN 2665-9131
Publisher: Elsevier
DOI: 10.1016/j.ocarto.2020.100069

Dynamic Compressive Loading Improves Cartilage Repair in an In Vitro Model of Microfracture: Comparison of 2 Mechanical Loading Regimens on Simulated Microfracture Based on Fibrin Gel Scaffolds Encapsulating Connective Tissue Progenitor Cells (opens in new window)

Author(s): Tomoya Iseki, Benjamin B. Rothrauff, Shinsuke Kihara, Hiroshi Sasaki, Shinichi Yoshiya, Freddie H. Fu, Rocky S. Tuan, Riccardo Gottardi
Published in: The American Journal of Sports Medicine, Issue 47/9, 2019, Page(s) 2188-2199, ISSN 0363-5465
Publisher: SAGE Publications
DOI: 10.1177/0363546519855645

Application of machine intelligence for osteoarthritis classification: a classical implementation and a quantum perspective (opens in new window)

Author(s): Dimitrios Tsaopoulos; Nikolaos Papandrianos; Elpiniki I. Papageorgiou; Christos Kokkotis; Serafeim Moustakidis; Eirini Christodoulou
Published in: Quantum Machine Intelligence, Issue 1, 2019, ISSN 2524-4914
Publisher: Springer
DOI: 10.1007/s42484-019-00008-3

Endothelial cells support osteogenesis in an in vitro vascularized bone model developed by 3D bioprinting (opens in new window)

Author(s): Irene Chiesa, Carmelo De Maria, Anna Lapomarda, Gabriele Maria Fortunato, Francesca Montemurro, Roberto Di Gesù, Rocky S Tuan, Giovanni Vozzi, Riccardo Gottardi
Published in: Biofabrication, Issue 12/2, 2020, Page(s) 025013, ISSN 1758-5090
Publisher: IOP Science
DOI: 10.1088/1758-5090/ab6a1d

Identification of Risk Factors and Machine Learning-Based Prediction Models for Knee Osteoarthritis Patients (opens in new window)

Author(s): Christos Kokkotis, Serafeim Moustakidis, Giannis Giakas, Dimitrios Tsaopoulos
Published in: Applied Sciences, Issue 10/19, 2020, Page(s) 6797, ISSN 2076-3417
Publisher: MDPI
DOI: 10.3390/app10196797

Stiffness modulation of redundant musculoskeletal systems (opens in new window)

Author(s): Dimitar Stanev, Konstantinos Moustakas
Published in: Journal of Biomechanics, Issue 85, 2019, Page(s) 101-107, ISSN 0021-9290
Publisher: Elsevier BV
DOI: 10.1016/j.jbiomech.2019.01.017

Modeling musculoskeletal kinematic and dynamic redundancy using null space projection (opens in new window)

Author(s): Dimitar Stanev, Konstantinos Moustakas
Published in: PLOS ONE, Issue 14/1, 2019, Page(s) e0209171, ISSN 1932-6203
Publisher: Public Library of Science
DOI: 10.1371/journal.pone.0209171

Early Weight-Bearing Improves Cartilage Repair in an in vitro Model of Microfracture: Comparison of Two Mechanical Loading Regimens on Simulated Microfracture Based onFibrin Gel Scaffolds Encapsulating Bone Marrow Mesenchymal Stem Cells: (opens in new window)

Author(s): Shinsuke Kihara; Riccardo Gottardi; Rocky S. Tuan; Freddie H. Fu; Benjamin B. Rothrauff; Shinichi Yoshiya; Tomoya Iseki
Published in: Orthopaedic Journal of Sports Medicine, Issue 1, 2019, ISSN 2325-9671
Publisher: SAGE journals
DOI: 10.5281/zenodo.3696673

A Machine Learning workflow for Diagnosis of Knee Osteoarthritis with a focus on post-hoc explainability (opens in new window)

Author(s): Christos Kokkotis; Serafeim Moustakidis; Elpiniki Papageorgiou; Giannis Giakas; Dimitrios Tsaopoulos
Published in: 2020
Publisher: IEEE
DOI: 10.1109/iisa50023.2020.9284354

A machine learning pipeline for predicting joint space narrowing in knee osteoarthritis patients (opens in new window)

Author(s): Charis Ntakolia, Christos Kokkotis, Serafeim Moustakidis, Dimitris Tsaopoulos
Published in: 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE), 2020, Page(s) 934-941, ISBN 978-1-7281-9574-2
Publisher: IEEE
DOI: 10.1109/bibe50027.2020.00158

Prediction of pain in knee osteoarthritis patients using machine learning: Data from Osteoarthritis Initiative (opens in new window)

Author(s): Antonios Alexos; Christos Kokkotis; Serafeim Moustakidis; Elpiniki Papageorgiou; Dimitrios Tsaopoulos
Published in: 2020
Publisher: IEEE
DOI: 10.1109/iisa50023.2020.9284379

The Effect of Kinematic and Dynamic Redundancy on the Assessment of Joint Reaction Loads

Author(s): D.Stanev, K. Moustakas
Published in: 2018
Publisher: Virtual Physiological Human (VPH) conference

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