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INTPART-International Partnerships for Excellent Education and Research

International Network for Image-based Diagnosis

Alternative title: International Network for Image-based Diagnosis

Awarded: NOK 4.5 mill.

INID will focus on networking at international level for training students, researchers and academic staff members acting in the fields of AI, Medical imaging and decision making. The outcomes of INID will lead to long-term top-class research in the field, turning Norway into a frontrunner in applying basic research on AI to healthcare. This project will build on the expertise of each of the partners to complement the peers´ competencies and to cooperate on the different tasks defined in the work plan. The scientific aim is to study how AI can help understand large collections of medical images and assist in diagnostic decisions made by the doctors or clinicians. Additionally, we will aim to make AI-based decision/diagnosis more understandable to clinicians and patients to ease the adoption of such tools in healthcare. This will be achieved through joint activities, including mobility stays, training schools, workshops, special sessions at international conferences and collaborative research work. This project builds on the ongoing H2020 ITN project HiPerNav and on AI4CDSS, a recently accepted RIA project called ALAMEDA is also supporting our network as it is about use of AI in healthcare for bridging the gap between diagnosis and treatment for dementia patients and stroke patients.

INID will focus on networking at international level for training students, researchers and academic staff members acting in the fields of AI, Medical imaging and decision making. The outcomes of INID will lead to long-term top-class research in the field, turning Norway into a frontrunner in applying basic research on AI to healthcare. This project will build on the expertise of each of the partners to complement the peers´ competencies and to cooperate on the different tasks defined in the work plan. The scientific aim is to study how AI can help understand large collections of medical images and assist in diagnostic decisions made by the doctors or clinicians. Additionally, we will aim to make AI-based decision/diagnosis more understandable to clinicians and patients to ease the adoption of such tools in healthcare. This will be achieved through joint activities, including mobility stays, training schools, workshops, special sessions at international conferences and collaborative research work. This project builds on the ongoing H2020 ITN project HiPerNav and on AI4CDSS, a recently submitted COST Action proposal on AI for decision making systems.

Activity:

INTPART-International Partnerships for Excellent Education and Research