Artificial intelligence capabilities for automated diagnosis and prediction of acute stroke outcomes based on magnetic resonance imaging

Abstract

Acute stroke is one of the leading causes of death and disability worldwide. Millions of people experience this disease every year, with significant consequences for both patients and health systems. Diagnosis and treatment of stroke require fast and accurate decision-making, as time is a critical factor for a successful outcome. However, existing diagnostic methods such as magnetic resonance imaging, although they provide high imaging accuracy, require significant time and human resources. This creates the need to develop new approaches that can improve the effectiveness of diagnosis and prediction of stroke outcomes. Artificial intelligence is actively developing and finding applications in various fields of medicine, including medical image analysis. The use of artificial intelligence to process MRI data opens up new possibilities for automated diagnosis and prediction of disease outcomes such as stroke. This improves diagnostic accuracy and reduces data analysis time, which is especially important in emergency situations.

Ähnliche Arbeiten