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SPKI is a centre for clinical artificial intelligence that facilitates implementation of AI in healthcare. SPKI has been established in collaboration between The University Hospital of North-Norway (UNN), UiT The Arctic University of Norway and Helse Nord RHF.
SPKI will put the patients and clinicians in focus, in the sense that innovation and implementation of clinical decision support tools based on artificial intelligence is considered to be equally important as the research activity of the centre. Artificial intelligence can only become useful for patients and clinicians if the new technology is implemented in clinical use – and this will be facilitated by SPKI.
The ambition of SPKI is to facilitate development and use of clinical decision support tools based on artificial intelligence by connecting clinical expertise with researchers on machine learning and technology.
To facilitate research, innovation and implementation of AI in the healthcare for the benefit of the patients and clinicians.
Disseminate knowledge about AI in health and give advice on technical and AI-related legal challenges.
Be a meeting place for clinicians and researchers with an interest in AI.
Disseminate knowledge, information, experiences, results.
Expertise in testing, validation and implementation of AI tools.
Participate in projects that facilitate implementation of AI.
Contribute to establishing open research databases consisting of de-identified health data.
Ensure collaboration across regions and health trusts.
Build networks and contribute to matchmaking.
Support projects in testing and implementing AI tools in the clinic.
Participate in R&D projects - from idea to implementation.
Channel inquiries about KI professional and legal challenges.
SPKI is established as a center at UNN and UiT, in collaboration with Helse Nord RHF, and SPKI is organizationally anchored in Fag- og kvalitetssenteret at UNN.
At UiT, the main contributors to the research activity of the center are the UiT Machine Learning Group and the SFI Visual Intelligence. Other contributors are e.g. The Health Data Lab, The Department of Clinical Medicine, and The Department of Social Sciences.
Network and cooperation are very crucial elements to succeed when working with research, innovation, and new technology. Hence, SPKI provides a list of networks and collaborators aiming to support anyone involved in AI for health to easily find and reach out to suitable collaborators.
Please note that the network listed below are non-comprehensive, if you have suggestions, please contact us.
The core strength of UiT Machine Learning Group is in basic research for advancing statistical machine learning & AI methodology to face the societal and industrial data-driven challenges of the future. The group has been doing research on machine learning for health and clinical AI for more than a decade and is a key contributor to the activity at SPKI.
Visual Intelligence is a Centre for research-based innovation that aims to be the lead provider of novel deep learning-based solutions for cutting-edge complex image analysis. One of the main innovation areas for Visual Intelligence is medicine and health. Visual Intelligence is advancing deep learning in medical imaging to solve challenges e.g. related with limited training data and explainability of black-box predictions. Hence, Visual Intelligence and SPKI operates in close synergy.
This is a large-scale interdisciplinary research consortium funded by UiT. Leveraging the development of new theory and methodological research, the aim of the consortium is to fill knowledge gaps between ML and organizational implementation of new solutions to translate basic, translational and clinical medical research, leading to high societal impact,
Kunstig intelligens i norsk helsetjeneste (KIN) is a national network for artificial intelligence in the health service, which connects professional environments from all over the country by establishing meeting places for joint discussion and exchange of knowledge about the implementation of artificial intelligence in the health sector. The network is open to anyone who wants to participate and share their work.
The Norwegian coordination project “Better use of artificial intelligence” is part of the work on the National Health and Hospital Plan 2020-2023, and will help and guide the health service so that it can succeed in using artificial intelligence in a safe way. The project is a collaboration between Helsedirektoratet, Direktoratet for e-helse, Statens legemiddelverk, Helsetilsynet, Folkehelseinstituttet, KS, and the regional health authorities.
CAI-X (Dansk center for klinisk kunstig intelligens/Danish Centre for Clinical Artificial Intelligence) is a joint center between the University of Southern Denmark (SDU) and Odense University Hospital (OUH). The center aims to ensure a close connection between patients, health care staff, researchers and engineering experts to bridge clinical challenges with technical expertise to provide new treatment solutions. SPKI has entered a strategic cooperation on clinical AI with CAI-X.
The Norwegian Centre for E-health Research will contribute to knowledge-based development in the area of e-health by means of research, collaboration and the dissemination of knowledge. The centre does research on all levels of health care: disease prevention, self-management, primary and specialist healthcare and rehabilitation.
As part of DIPS AS, Norway’s leading vendor of e-health solutions, the DIPS Research and Innovation department aims to improve electronic health record systems by applying findings from research into AI, natural language processing and IoT devices. It also aims to facilitate new patient-oriented AI applications by providing standardized interfaces and open testing environments for its products.
The Health Data Lab is hosted by UiT, and aims to provide the systems, methods, and tools needed to analyse and interpret complex health datasets. The activities at the Lab are mainly threefold; build and experimentally evaluate infrastructure systems for bioinformatics and machine learning analyses, apply bioinformatics, statistics, and machine learning methods for novel health data analyses, and build and evaluate data exploration and interpretation tools.
180°N – Norwegian Nuclear Medicine Consortium aims to strengthen research in nuclear medicine connected to the nuclear medicine equipment donated by Trond Mohn Foundation and Tromsø Research Foundation to the universities and hospitals in Trondheim, Tromsø and Bergen.
The GEMINI center MIRA: Medical Imaging Research and AI is established to bring together researchers and clinical experts working with medical image analysis at NTNU, St. Olavs hospital, and SINTEF. The center focuses on artificial intelligence applications for MR, ultrasound, and CT imaging.
CAIR – Centre for Artificial Intelligence Research is hosted by the Department of ICT at the University of Agder. The centre was opened on 2nd of March 2017 and aims to address unsolved problems and push the research frontier, seeking superintelligence by providing an attractive environment for cutting-edge research.
The Artificial intelligence and digital pathology in cancer (AICAN) is a cross disciplinary research group, which incorporates NTNU, St. Olavs hospital, Levanger hospital and SINTEF. The group aims to explore the application of artificial intelligence for interpreting histopathological slides from cancer.
The Mohn Medical Imaging and Visualization Centre (MMIV) is a joint centre between the University of Bergen and the Haukeland University Hospital. The centre aims to research new methods in quantitative imaging and interactive visualization so as to predict changes in health and disease across spatial and temporal scales, which encompasses research in tissue feature detection, feature extraction and feature prediction.
CRAI group at Oslo University Hospital act as a research hub within the Division of Radiology and Nuclear Medicine, with research group members spanning a wide range of disciplines and research areas, who are interested in using AI and other advanced computational tools as an integral part of their research.
The Norwegian Open Artificial Intelligence Lab (NAIL) centre is located in Trondheim, and hosted by NTNU, Faculty of Information Technology and Electrical Engineering. NAIL is a hub for research, education, and innovation within AI.
The Institute for Cancer Genetics and Informatics (ICGI) is a department within the Division of Cancer Medicine at Oslo University Hospital (OUS). The ICGI research applicability and uses of artificial intelligence so as to develop method for cancer treatment focusing on digital image analysis. The goal is to enable better cancer treatment through diagnostics based on artificial intelligence (AI).
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