Seminar data and AI

Cross collaboration seminar about data and AI usage in pre-hospital stroke care decision making

​This is a seminar about cross-collaboration, potential, challenges related to the data and AI usage in pre-hospital stroke care decision making in Nordic countries and Singapore.

This is a seminar about cross-collaboration, potential, challenges related to the data and AI usage in pre-hospital stroke care decision making in Nordic countries and Singapore. – What has been done, What should be done, What are the challenges and How can we overcome the challenges together?

It is known that nowadays chronic diseases impose an enormous financial and societal burden on the world.
Stroke, or cerebrovascular accidents (CVA), are caused by either a sudden reduction in the blood supply to the
brain due to cerebral infarction (a clot, 85% of patients), or by rupture of a blood vessel or aneurysm in the brain (bleeding, 15% of patients). Stroke is the second leading cause of death and disability in Europe after ischemic heart disease, accounting for 405,000 deaths (9%) in men and 583,000 (13%) deaths in women each year. Minimizing time to definitive care is the key to effective stroke treatment.

In recent years the treatments for stroke have vastly improved, especially with the introduction of thrombectomy that can cure patients with large vessel occlusion effectively by mechanically removing the clot, a specialized intervention often only available at university hospitals. The main challenge to provide the best possible care for stroke patients today is to improve the precision in recognizing stroke and its subtypes already before arrival to hospital, so that time to the most suitable treatment (in the most suitable hospital) is decreased.

Data and Artificial Intelligence (AI) generally has great potential to be used as decision making support for
patient management and treatment. For stroke, a critical decision making applies to the most suitable transport destination for the patient. There is large interest in investigating whether an AI, fusion of different types of data such as known medical history, age, gender, vital data, microwave diagnostic data, EEG, and sound/video, can improve the accuracy of the management of stroke patients. Using heterogeneous data together with AI is definitely an opportunity but in practice, making this happen is challenging and require ecosystemic, interdisciplinary, cross country collaboration and ability to solve the data safety and security issues in a right manner.

The aim of this seminar is to bring together experts from hospitals, companies and research organizations in
between Nordic countries and Singapore in order to discuss about the pre-hospital stroke care decision making. What has been done, What should be done, What are the challenges and How can we overcome the challenges together?

Kategori Seminarium
Plats: Online
Tid: 2021-10-14 08:00
Sluttid: 2021-10-14 12:00

Sidansvarig Publicerad: to 26 aug 2021.