MOMIS
Virtual integration of data collected from clinical databases
MOMIS is an open source framework developed by DataRiver able to semi-automatically integrate, using semantics, clinical Big Data from heterogeneous, structured data sources (such as hospital medical records, clinical registers, eCRF systems, laboratory databases and other databases clinical) and semi-structured (e.g. spreadsheet, json, xml), bringing out new clinical information from existing and apparently unrelated data. The discovery of the relationships between the schemes of the information sources exploits the semantics present in the source data and makes use of clustering and inference techniques of the descriptive logics.
MOMIS makes it possible to obtain new information on patients by integrating data already present in the various clinical databases with information collected directly from the patient thanks to the use of:
– Medical devices for the monitoring of physiological parameters
– Wearable devices and sensors for collecting data on physical and rehabilitative activity performed by patients
– App on smartphone / tablet for the collection of Electronic Patient Report Outcomes (ePRO)
– Vocal assistant and ChatBot
FEATURES
1) AUTOMATION OF THE DATA INTEGRATION PROCESS
Automation of the data integration process by exploiting Semantics and applying Machine Learning and Artificial Intelligence (AI) techniques, ensuring high flexibility, scalability and consequent reduction of costs and time for data integration.
2) VIRTUAL APPROACH AND DATA COLLECTION IN ANONYMIZED FORM
Data integration in a completely anonymized form. This approach allows the development of retrospective clinical studies by collecting data in anonymized form, making the integration without performing a centralized copy of the data, while preserving the autonomy and security of the original information sources.
3) GUARANTEE OF SECURITY OF DATA SOURCES
Guarantee of security of the original data sources in compliance with the regulations in force for the management of personal data and sensitive data.
4) BIG DATA ANALYSIS THROUGH ARTIFICIAL INTELLIGENCE
The integrated and standardized / standardized data collected from the different data sources allow to carry out an advanced analysis through the use of Machine Learning and Artificial Intelligence algorithms with the aim of carrying out a multidimensional monitoring of patients, supporting a correct understanding of clinical manifestations and planning personalized treatment paths.
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