Abstract
Digital technologies are changing the field of medicine and health. Ubiquitous medical devices can be used as point-of-care tools to measure and timely deliver personalized medical treatments across the whole continuum of care. However, this comes with a number of technical and medical challenges that will guide the research and development of digital health technologies in the coming years. In this talk I will highlight how medical automation and artificial intelligence can open new avenues to enable easy access to medical technology outside specialized clinical centers and to personalize treatment. How can high quality clinical decisions be made outside the strongly controlled medical environment? I call for intelligent user-machine interaction where difficult or error-prone tasks are delegated to the device. Automated, closed-loop methodologies together with machine learning approaches will have a huge impact on future medical technologies and will find applications in many medical domains, from prevention to treatment.
Digital technologies are changing the field of medicine and health. Ubiquitous medical devices can be used as point-of-care tools to measure and timely deliver personalized medical treatments across the whole continuum of care. However, this comes with a number of technical and medical challenges that will guide the research and development of digital health technologies in the coming years. In this talk I will highlight how medical automation and artificial intelligence can open new avenues to enable easy access to medical technology outside specialized clinical centers and to personalize treatment. How can high quality clinical decisions be made outside the strongly controlled medical environment? I call for intelligent user-machine interaction where difficult or error-prone tasks are delegated to the device. Automated, closed-loop methodologies together with machine learning approaches will have a huge impact on future medical technologies and will find applications in many medical domains, from prevention to treatment.
Bio
Walter Karlen is an Assistant Professor at the Department of Health Sciences and Technology, and Head of the https://www.bi.id.ethz.ch/eAdressen/ at ETH Zurich in Switzerland. He received his Master degree in micro-engineering from the http://www.epfl.ch/, Switzerland in 2005 and obtained his PhD from the doctoral program in Computer, Communication and Information Sciences at EPFL in April 2009. For his PhD, Karlen joined the http://lis.epfl.ch/ under the supervision of Prof. Dario Floreano. He was a scientific consultant for physiological monitoring in extreme environments for http://www.solarimpulse.com/, Switzerland. From April 2009 to October 2014, Karlen was a post-doctoral researcher at the University of Stellenbosch, South Africa and the University of British Columbia in Vancouver, Canada where he worked on http://www.ece.ubc.ca/~walterk/#ResearchProjects and novel algorithms for automated analysis of biomedical signals during anesthesia.
Walter Karlen is an Assistant Professor at the Department of Health Sciences and Technology, and Head of the https://www.bi.id.ethz.ch/eAdressen/ at ETH Zurich in Switzerland. He received his Master degree in micro-engineering from the http://www.epfl.ch/, Switzerland in 2005 and obtained his PhD from the doctoral program in Computer, Communication and Information Sciences at EPFL in April 2009. For his PhD, Karlen joined the http://lis.epfl.ch/ under the supervision of Prof. Dario Floreano. He was a scientific consultant for physiological monitoring in extreme environments for http://www.solarimpulse.com/, Switzerland. From April 2009 to October 2014, Karlen was a post-doctoral researcher at the University of Stellenbosch, South Africa and the University of British Columbia in Vancouver, Canada where he worked on http://www.ece.ubc.ca/~walterk/#ResearchProjects and novel algorithms for automated analysis of biomedical signals during anesthesia.