eHealthNet – ICAR

Involved Laboratories:

Selected Publications:

M. Pota, M. Esposito, G. De Pietro, “Likelihood-fuzzy analysis: From data, through statistics, to interpretable fuzzy classifiers”. International Journal of Approximate Reasoning, vol. 93, pp. 88-102, ISSN 0888-613X, DOI 10.1016/j.ijar.2017.10.022, 2018

A. Amato and A. Coronato, “An IoT-aware architecture for smart healthcare coaching systems”, Proceedings of the 2017 IEEE 31st International Conference on Advanced Information Networking and Applications (AINA), IEEE, 2017, DOI: 10.1109/AINA.2017.128, AINA-2017

G. De Pietro, M. Ciampi, G. Iorio, R. Capasso, G. Antonucci, M. Barile e M. G. Rosa, “La salute in rete tra eccellenza e innovazione”, Leda Editore, pp. 1-64, 2017, ISBN: 978-88-970-0558-2

C. Diomaiuta, M. Sicuranza, M. Ciampi, and. G. De Pietro, “A FHIR-based system for the generation and retrieval of clinical documents”, in ICT4AWE 2017: Proceedings of the 3rd International Conference on Information and Communication Technologies for Ageing Well and e-Health, Volume 1, pp. 135-142, 2017, SCITEPRESS Digital Library, ISBN: 978-989-758-251-6, DOI: 10.5220/0006311301350142

M. Pota, M. Esposito, G. De Pietro, “Designing rule-based fuzzy systems for classification in medicine”, Knowledge-Based Systems, vol. 124, pp. 105-132, ISSN 0950-7051, DOI 10.1016/j.knosys.2017.03.006, 2017

G. Sannino, I. De Falco, and G. De Pietro, “A statistical analysis for the evaluation of the use of wearable and wireless sensors for fall risk reduction”, Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies, Volume 5: SmartMedDev, BIOSTEC 2017, pp. 508-516, 2017

S. Naddeo, L. Verde, M. Forastiere, G. De Pietro, and G. Sannino, “A real-time m-health monitoring system: an integrated solution combining the use of several wearable sensors and mobile devices”, Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies, Volume 5: SmartMedDev, BIOSTEC 2017, pp. 545-552, 2017

G. Caggianese, M. Calabrese, V. De Maio, G. De Pietro, A. Faggiano, L. Gallo, G. Sannino, and C. Vecchione, “A rehabilitation system for post-operative heart surgery”, Proceedings of the International Conference on Intelligent Interactive Multimedia Systems and Services, pp. 554-564, Springer, Cham, 2017

G. Caggianese, M. Calabrese, L. Gallo, G. Sannino, C. Vecchione, “Cardiac Surgery Rehabilitation System (CSRS) for a Personalized Support to the Patients”, In Proceedings of the 13th 2017 International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), 2017

A. Amato and A. Coronato, “Supporting hypothesis generation by machine learning in smart health”, Springer International Publishing AG 2018, L. Barolli and T. Enokido (eds.), Innovative Mobile and Internet Services in Ubiquitous Computing, Advances in Intelligent Systems and Computing 612, DOI: 10.1007/978-3-319-61542-4 38, IMIS-2017

A. Amato and A. Coronato, “A machine learning approach for ranking in question answering”, in Xhafa F., Caballé S., Barolli L. (eds), Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2017. Lecture Notes on Data Engineering and Communications Technologies, vol. 13, Springer, Cham, 2017

A. Coronato and G. Paragliola, “Towards a Cognitive System for the Identification of Sleep Disorders”, Proceedings of the International Conference on Intelligent Interactive Multimedia Systems and Services, pp. 91-98, 2017

A. Minutolo, M. Esposito, G. De Pietro, “A fuzzy framework for encoding uncertainty in clinical decision-making”, Knowledge-Based Systems, vol. 98, pp. 95-116, ISSN 0950-7051, DOI 10.1016/j.knosys.2016.01.020, 2016

M. Pota, M. Esposito, G. D. Pietro, “Interpretability indexes for Fuzzy classification in cognitive systems”, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 24-31, ISBN 978-1-5090-0626-7, DOI 10.1109/FUZZ-IEEE.2016.7737663, Vancouver, BC, Canada, 24-29 Luglio 2016

A. Minutolo, M. Esposito, G. De Pietro, “Fuzzy on FHIR: a Decision Support service for Healthcare Applications”, in Advances on P2P, Parallel, Grid, Cloud and Internet Computing, 3PGCIC 2016 (F. Xhafa, L. Barolli, F. Amato, eds.), Lecture Notes on Data Engineering and Communications Technologies, vol. 1, pp. 163-172, Springer International Publishing, ISBN 978-3-319-49109-7, DOI 10.1007/978-3-319-49109-7_16, 2016

A. Minutolo, M. Esposito, G. De Pietro, “A Hypothetical Reasoning System for Mobile Health and Wellness Applications”, in Wireless Mobile Communication and Healthcare: MobiHealth 2016 (P. Perego, G. Andreoni, G. Rizzo, eds.), Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 192, pp. 278-286, Springer International Publishing, ISBN 978-3-319-58877-3, DOI 10.1007/978-3-319-58877-3_36, 2016

A. Minutolo, M. Esposito, G. De Pietro, “Encoding Clinical Recommendations into Fuzzy DSSs: An Application to COPD Guidelines”, in Knowledge, Information and Creativity Support Systems: Recent Trends, Advances and Solutions (A. M. J. Skulimowski, J. Kacprzyk, eds.), Advances in Intelligent Systems and Computing, vol. 364, pp. 345-357, Springer International Publishing, ISBN 978-3-319-19089-1, DOI 10.1007/978-3-319-19090-7_2, 2016

G. Sannino, I. De Falco, and G. De Pietro, “Easy fall risk assessment by estimating the Mini-BES test score”, Proceedings of the 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom), IEEE, 2016

M. Mercorella, M. Ciampi, M. Esposito, A. Esposito, and G. De Pietro, “An architectural model for extracting FHIR resources from CDA documents”, in SITIS 2016: Proceedings of 12th International Conference on Signal-Image Technology & Internet-Based Systems, pp. 597-603, 2016, IEEE Computer Society, ISBN: 978-1-5090-5698-9, DOI: 10.1109/SITIS.2016.99

eHealthNet: Ecosistema software per la Sanità Elettronica.

START DATE November 2013
END DATE April 2017

Site: http://www.ehealthnet.it/

The project was presented as part of the National Operational Program “Research and Competitiveness” 2007-2013 (PONR&C) for the Convergence Regions, Action “Public-private laboratories and related networks”. The Laboratory that carried out the project includes 2 major companies, 10 SMEs, 6 Research Bodies and 2 Universities. The CNR Institutes involved were ICAR, IBB, IMM, and IBP. The project aimed to design and implement a software ecosystem consisting of models, services, and tools for the implementation of applications to support diagnosis, therapy, and follow-up, as well as for the innovative management of health processes. This ecosystem, acting as a collector of all the actors that interact in various ways in social and health processes, was conceived with the aim of facilitating data integration, real-time alignment, advanced interoperability, and cooperation between the various public and private actors in compliance with the standards of the sector. The developed ecosystem has included a broad spectrum of ICT technologies, services, and tools functional to the health system, essentially aimed at supporting the need for change by working on four lines of intervention: interoperability, necessary to make the existing applications able to communicate each other and to interconnect structures and data, guaranteeing security, privacy, and confidentiality (interoperable eHealth); reliable telemonitoring and telemedicine systems (pervasive eHealth); knowledge technologies to support diagnosis, therapy, and rehabilitation health processes for the rationalization and control of healthcare expenditure (sustainable eHealth); predictive medicine, aimed at early diagnosis and achieving a correct lifestyle (preventive eHealth). In order to achieve these goals, the software ecosystem has been organized into infrastructure services, technology platforms, and meta-services. The technological platforms implemented are capable of managing health processes, supporting clinical decisions, mobile healthcare, signal analysis, image diagnostics, advanced visualization, behavioral analysis, virtual rehabilitation, health information systems management, management of medical information in social networking. At the end of the project, 7 demonstrators were developed for experimenting the effectiveness of the eHealthNet ecosystem realized in operating conditions similar to the real ones.