Thanks to the emerging technologies of e-Learning, the analysis of data offers professionals in the education sector, advantages with the ability to impact and revolutionize in the future the way we analyze and evaluate the learning experience.
Diagnosis aid system based on computer vision
Intestinal motility disorders (contractions), which are usually characterised by rhythmic changes and uncoordinated movements of the intestinal tract, affect up to 30% of the population and can have major implications for their quality of life.
GCD@UB, the company Given Imaging and gastroenterology specialists from Vall d’Hebron University Hospital developed a system for diagnosing intestinal motility disorders based on images taken by a wireless endoscope camera that describes a range of visual patterns, both static and dynamic, from which an objective diagnosis can be made.
From a medical point of view, the research focused on identifying new factors that are symptomatic of the disease based on the visual analysis of images. From a technology perspective, the innovation lies in the development of an automatic recognition system that instantly extracts visual diagnostic patterns from a large number of images, and the creation of an automatic decision-making system to assist doctors with their diagnoses. This development finally paves the way for replacing the current methodology, which causes patient discomfort, with a more comfortable alternative that presents improved diagnostic capabilities.
Within the framework of the Cartographic Plan of Catalonia, the Cartographic and Geological Institute of Catalonia is working on the elaboration of the technical specifications of the land covers Map of Catalonia. The ICGC has commissioned us a study to explore the viability of the application of deep learning techniques in the generation of maps.
A company in the online sector has generated a large volume of data that provides a history to be able to extract information from clients and develop a predictive model based on the behavior of users. This behavior include the navigation through the platform, the interaction with others channels, messages to the community, etc. The ultimate goal is to provide a better customer service by recommending products based on the specific time of the customer journey.