Date(s) - 03/03/2015
18:30 - 21:00
ETH Zürich - CAB Building
Marc Pouly speaks on Detection and Quantification of Skin Eczema by Visible Spectrum Skin Pattern Analysis at a joint meeting of SGAICO and the Zurich Machine Learning and Data Science Meetup Group. See www.meetup.com/Zurich-Machine-Learning/ for last minute room information.
We are proud to announce another interesting talk within our SGAICO Forum series.
This time, we meet jointly with the Zurich Machine Learning and Data Science Meetup group (see http://www.meetup.com/Zurich-Machine-Learning/).
The talk is followed by drinks and snacks sponsored by SGAICO.
Marc Pouly, Hochschule Luzern
Detection and Quantification of Skin Eczema by Visible Spectrum Skin Pattern Analysis
Eczema are frequent dermatoses with severe health and financial consequences to patients and society. They follow a chronic course and may persist for long periods of time after onset. A new generation of highly effective drugs has recently been pushed onto the market, but due to the exorbitant costs of this new treatment, health insurances cover expenses only in severe cases. Dermatologists have therefore been developing different scoring systems to objectively measure and document eczema severeness. However, assessing the parameters for these scores in practice is difficult as it for example requires to estimate the percentage of body surface with eczema infestation. In this talk we present a prototype-based feasibility study of automated detection and quantification of skin eczema using texton-based imaging and machine-learning techniques; a multi-disciplinary research project between the university hospitals of Zurich and the Lucerne university of applied sciences and arts.
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