30 million people across Europe are affected approximately from rare diseases. The brain disorders (including, but not limited to those affecting mental health) remain a major challenge. The understanding of mental disorders’ determinants and causes, processes and impacts is a key to their prevention, early detection and treatment as well as factor for good health and well-being. In order to improve the health and disease understanding, a close linkage between fundamental, clinical, epidemiological and socio-economic research is required. Effective sharing of data, standardized data processing and the linkage of such data with large-scale cohort studies is a prerequisite for translation of research findings into the clinic. In this context, this paper proposes a platform for exploration of behavioral changes in patients with proven cognitive disorders with a focus on Multiple Sclerosis. It adopts the concept of a digital twin by applying the Big Data and Artificial Intelligence technologies to allow for deep analysis of medical data to estimate human health status, accurate diagnosis and adequate treatment of patients. The platform has two main components. The first component, provides functionality for diagnostics and rehabilitation of Multiple Sclerosis and acts as a main provider of data for the second component. The second component is an advanced analytical application, which provides services for data aggregation, enrichment, analysis and visualization that will be used to produce a new knowledge and support decision in each instance of the transactional component.
Abstract. Semantic 3D city models are increasingly applied for a wide range of analysis and simulations of large urban areas. Such models are used as a foundation for development of city digital twins, representing with high accuracy the landscapes and urban areas as well as dynamic of the city in terms of processes and events. In this context, this paper presents a 3D city model, which is a starting point for development of digital twin of Sofia city. The 3D model is compliant with CityGML 2.0 in LOD1, supporting integration of the buildings and terrain and enriching the buildings’ attributes with address information. District Lozenets of Sofia city is chosen as a pilot area for modelling. An approach for 3D transformation of proprietary geospatial data into CityGML schemas is presented. The integration of the buildings and terrain is an essential part of it, since the buildings often partially float over or sink into the terrain. A web application for user interaction with the 3D city model is developed. Its main features include silhouetting a single building, showing relevant overlay content, displaying shadows and styling of buildings depending on their attributes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.