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Medical data becomes available as part of normal medical practice in hospitals, or in research environments as part of controlled experiments. We will discuss the general approach of using machine learning and data science to create novel findings and predictions from biomedical data and electronic health records. We will describe some of our research case studies in the analysis of cancer genomics data and in diagnostic prediction in neonatal intensive care unit. These case studies will highlight the intertwining of data science with the medical domain in order to create novel and useful knowledge to benefit medical science. Time allowing, I will discuss an experimental prototype of photograhic foot imaging device and the possible future development towards a system for assesssing the state of feet in diabetes patients.
Jaakko Hollmén (b. 1970) received the degrees of M.Sc. (Tech.) in 1996, Lic.Sc. (Tech.) in 1999, and D.Sc. (Tech.) in 2000, all at the Department of Computer Science and Engineering at the Helsinki University of Technology in Finland. Currently, He is faculty member at Department of Computer Science at Aalto University in Espoo, Finland. Jaakko Hollmén's research interests include theory and practice of machine learning and data science. He is especially keen in applying the novel methodologies in health and wellbeing area as well as environmental informatics area. He has taken part in organization of many conferences in machine learning, intelligent data analysis. Currently, he has taken part in organizing the 32nd IEEE CBMS International Symposium on Computer-Based Medical Systems, taking place in Cordoba, Spain during June 5-7, 2019
Actividad realizada en el marco del proyecto DPI2015-69891-C2-2-R, financiada por el Ministerio de Economía y Competitividad (MINECO), Programa Estatal de I+D+i Orientada a los Retos de la Sociedad y por el Fondo Europeo de Desarrollo Regional (FEDER) "Una manera de hacer Europa" |