• celebrado en Sala de Grados A; E.T.S.I. Informática, el 28/06/2017, 11:00

  • The abundance of biomedical, biological and clinical data has created the need for more effective
    methods for processing, querying, analytics, and interpretation. Specifically, due to the
    emergence of novel medical monitoring technologies and portable health monitoring devices in
    many health and clinical applications, the complexity and size of biological and physiological
    data have created the challenge of processing / analyzing of the abundance of these data. In a
    variety of clinical applications, the abundance of sensors designed for collecting biomedical
    signals, images and videos have created the challenge of analyzing and integrating the
    knowledge in these modalities. In majority of these applications, the main challenges are: 1)
    processing the raw data to extract informative features from signals, images or videos, 2)
    applying machine learning to the best set of identified features to create predictions and
    recommendations for clinical decision making. In this talk, our computational solutions for these
    challenges for a few clinical applications will be discussed.