m-Resist is a research & innovation project funded by the EU under the Horizon 2020 programme. M-Resist aims to develop an innovative disease management system addressed to empower patients suffering from treatment resistant schizophrenia, which will involve them to actively participate in the therapeutic process and will enable them to self-manage their condition, as well as to support their careers. m-RESIST will become a step forward in improving and optimizing the clinical decision process.
The specific aims for developing the m-RESIST are:
Design and develop the m-RESIST system.
Design the m-RESIST programme (services, care pathways or health routes).
Introduce m-RESIST system to schizophrenic resistant patients and monitor the effect of the system.
Assess acceptability of m-RESIST interfaces in terms of usability, accessibility, satisfaction, and perceived usefulness and appropriateness; by identifying dissonances between end-users needs and m-RESIST responses to those needs, as well as dissonances in parameters related to treatment effectiveness; by readjusting m-RESIST programme according to the suggestions of patients and caregivers.
Create a predictive model based on a wide range of relevant data gathered by the system in order to identify risks and gaps in the treatments which will enable the prescription of personalised treatment and tools for patients, for managing co-morbidities and healthcare.
Figure 1. m-Resist Overview
m-Resist Impact for ICCS / NTUA :
Through m-Resist we were able to gain first hand experience in the Health industry and how emerging technologies are being used and adopted is a vast array of medical fields. Even though m-Resist is focused at treatment resistant schizophrenia patients, through our partnership with large Health institutions we can envision our tools to be used in other contexts. Specifically we:
- Developed a centralized repository focused at the storage of Patient records in a distributed manner.
- Developed a Health Recommender System which provides three types of recommendations.
- Actions which the Patient should perform;
- Actions which the Caregiver should perform;
- Actions which the system should trigger.
- Created a weighted model for Patient similarity which can be configured to work in different health contexts and is the basis for the recommendation system.
- Supported the research of two experienced, postdoctoral researchers (E. Bothos, B. Magoutas)
- Supported the doctoral research of one PhD student (F. Paraskevopoulos).
Project website: www.mresist.eu
See the m-RESIST Leaflet: leaflet_m-RESIST
Project information: info_m-RESIST
For more information please contact at ECE NTUA: G. Mentzas (Professor), Tel.: +30 210 7722415, Email address: email@example.com