Overlegen nr. 4 - 2016

OVERLEGEN 4-2016 45 modal analytics, clinical knowledge and reasoning capabilities [4], [5, 6]. Artificial intelligence will facilitate introduction of Personalised Medicine Personalised Medicine is an emerging approach for disease treatment and prev- ention that takes into account individual variability in genes, environment, and lifestyle for each person [5]. Computational systems can eventually offer patients with a fast and efficient healthcare sys- tem for both diagnosis and treatment. One example where computational systems play a central part is the Cancer Moonshot initiative in the United States, called by President Obama in his 2016 State of the Union Address [7], aiming to eliminate cancer to achieve a decade’s worth of progress in 5 years. The collaboration between Lawrence Livermore National Laboratory and Norwegian Cancer Registry is a part of this strategy [8]. The project, facilitated by Oslo Cancer Cluster, is aiming to optimize cancer screening by using machine learning and neural networks to look at historical data [9]. Computer-aided diagnosis methods have recently become a part of the routine clinical work with the help of emerging digital assistant technologies [10]. Digital assistant technologies for efficient and faster diagnosis towards disease prevention - anticipating a world where diseases are minimized or avoided entirely. The penetration of IT into healthcare also helps to reduce medication errors and streamline infection-prevention protocols [11]. One example is when sensors capture measurements when a tumor flares up again after treatment at an early stage. Another is to improve prevention by insights to minimize the risks based on learning from larger groups.Thanks to analytics, interoperability and latest technological innovations [12] – major tech players are getting involved in the digital health race and more companies are investing on how to integrate smart sensors, connected devices and digital assistants into diagnostic labs and clinics. IBMWatson, a cognitive computing platform, is one example. It uses natural language processing and machine learning to reveal insights from large amounts of unstructured data [13]. The system, analyses high volumes of data, understands complex questions posed in natural language, and proposes evidence-based answers. Norway should take a clear position in digital health A decade ago none of us could have imagined that the mobile technology can create a database with the wisdom of our own body. Just from a smart watch, data ranging from blood pressure to heartbeat can be recorded on a real-time basis and data of an individual can be monitored on a long term basis. This kind of patient generated data can be obtained easily and longitudinally, over the course of a lifetime, creating the concept of ‘long data’ [14]. This comes on top the ‘big data’ concept that gained

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