The VIKING project Veien Til Kunstig Intelligens I Klinisk Nevrofysiologi.
In the VIKING project, our goal is to establish the world’s largest database of clinical neurophysiological data within an open infrastructure designed to facilitate research and AI development. Additionally, we aim to develop a user-focused roadmap for creating and implementing AI-based decision support systems to advance the diagnosis and management of neurological diseases.
Background
Norway is in a unique international position due to the high level of standardization between hospitals and laboratories, allowing for the compilation of large volumes of clinical data. In the VIKING project, we plan to collect data from more than 11 hospitals in Norway, representing an estimated 500,000 patients. Additionally, we will incorporate substantial contributions of annotated data from Sweden and the Netherlands, totaling 700,000 patients, to create the world’s largest database of clinical neurophysiological data.
We will also leverage Norway’s health registers by integrating our clinical neurophysiological data with these health register datasets. Norway’s health registers are among the most comprehensive in the world, offering a wealth of high-quality data spanning several decades. These registers provide unparalleled insights into disease patterns and treatment outcomes across the population, creating a unique opportunity to drive healthcare advancements through data-driven research and innovation.
Artificial intelligence (AI) is set to transform healthcare, driven by advancements in analytical techniques and computational power. AI has the potential to uncover clinically significant insights hidden within vast amounts of medical data, thereby enhancing clinical decision-making. By harnessing health data and integrating diverse data sources, AI can enable precision medicine, improve patient outcomes, and provide real-time decision support by identifying patient-specific patterns of disease progression.
The VIKING project second work package is split into 3 sections: The first section focuses on clinicians' and patients' knowledge, perspectives, attitudes, expectations, thoughts, and trust regarding AI-based decision support systems in clinical neurophysiology. The second section addresses the ethical challenges we face and how these can be mitigated. The third section consolidates this new knowledge into a user-oriented roadmap for the development and implementation of AI-based decision support systems for neurological diseases diagnosed through neurophysiological examinations.
Milestones:
- Establish the necessary IT infrastructure for secure, legal, and ethically responsible data processing
- Establish data processing agreements and collect neurophysiological data from up to 500,000 patients in Norway, and 100,000–200,000 from abroad.
- Connect to patient registers, preprocess and prepare the data. Establish a protocol for prospective data collection.
The project aim to answer the questions:
- What knowledge, perspectives, expectations, and attitudes do users (patients, clinicians) have regarding the introduction of an AI-based decision support system for neurophysiological examinations?
- How can we promote trust in AI-based decision support systems among users (patients, clinicians)?
- What ethical challenges exist for the development, testing, and implementation of AI-based decision support tools for neurophysiological examinations, and how can they be addressed?