Singular Logic (SiLo) is the leading Greek Enterprise Software Solutions provider and one of the largest Integrated IT Solutions Groups in Greece with extended expertise on the design, development and deployment of cloud-based enterprise software systems and applications through the participation in a several ICT R&D projects and IT solutions for private sector.
Within CrowdHEALTH, SiLo is responsible for the development of two core components of the data ingestion and data integration tiers of the CrowdHEALTH platform, namely the Data Sources and Gateways and the Data Cleaner components. The scope of the Data Sources and Gateways component is to deliver the software tool supporting the process of acquiring multimodal data from various sources and various providers, which may be described in different and often inconsistent formats. The Data Sources and Gateways facilitates the resolution of the connectivity and communication challenges with such information sources, by providing an abstracted and unified API which supports the acquisition of information from these sources and by handling the interaction with the rest of the internal components of the CrowdHEALTH architecture to orchestrate the data ingestion process of the platform.On the other hand, the scope of the Data Cleaner component is to deliver the software implementation that provides the assurance that the provided datasets coming from the several heterogeneous data information sources are clean and complete, to the extent possible. Thus, the Data Cleaner provides the processes that detect and correct (or remove) inaccurate or corrupted datasets containing incomplete, incorrect, inaccurate or irrelevant data elements with the purpose of replacing, modifying or deleting these data elements, also known as “dirty” data. Additionally, SiLois in charge of designing and implanting one of the Health Analytics Tools developed within the context of the CrowdHEALTH platform. More specifically, the specific tool developed by SiLo provides effective risk analysis and opportunities for policy making in the context of CrowdHEALTH in the case of pulmonary fibrosis exacerbation and the associated mortality risk estimation. Within this context, a machine learning model has been trained and employed and the Gradient Boosting framework has been exploited.
Besides the described development activities, SiLo being a commercial entity has a leading role in the exploitation activities of the project, including the development of business and marketing plans, but also the conduction of the prerequisite market and financial analysis.