ZULUAGA , Maria

In the travel industry, online customers book their travel itinerary according to several features, like cost and duration of thetravel or the quality of amenities. To provide personalized recommendations for travel searches, an appropriate segmentation of customers is required. Clustering ensemble approaches were developed to overcome...

In order to provide personalized recommendations for travel search queries to online customers, an appropriate segmentation of customers is required using information from the search query. Clustering ensemble approaches have been developed to overcome well-known problems of classical clustering approaches, that each rely on a different...

While federated learning is the state-of-the-art methodology for collaborative learning, its adoption for training segmentation models often relies on the assumption of uniform label distributions across participants, and is generally sensitive to the large variability of multi-centric imaging data. To overcome these issues, we propose a novel...

A limiting factor towards the wide real-life use of wearables devices for continuous healthcare monitoring is their cumbersome and obtrusive nature. This is particularly true for electroencephalography (EEG) recordings, which require the placement of multiple electrodes in contact with the scalp. In this work we propose to identify the optimal...

Background: Telemedicine has the potential to revolutionize healthcare. While the development of digital health technologies for the management of patients with cardiovascular diseases has been increasingly reported, applications in vascular surgery have been far less specifically investigated. The aim of this review is to summarize...

Deep learning techniques for 3D brain vessel image segmentation have not been as successful as in the segmentation of other organs and tissues. This can be explained by two factors. First, deep learning techniques tend to show poor performances at the segmentation of relatively small objects compared to the size of the full image. Second, due...

Today's growing medical image databases call for novel processing tools to structure the bulk of data and extract clinically relevant information. Unsupervised hierarchical clustering may reveal clusters within anatomical shape data of patient populations as required for modern Precision Medicine strategies. Few studies have applied...