부산대학교 도서관

Background: Acute ischemic stroke (AIS) is an immediate emergency whose management is becoming more and more personalized while facing a limited number of neurologists with high expertise. Clinical decision support systems (CDSS) are digital tools leveraging information and artificial intelligence technologies. Here, we present the Strokecopilot project, a CDSS for the management of the acute phase of AIS. It has been designed to support the evidence-based medicine reasoning of neurologists regarding the indications of intravenous thrombolysis (IVT) and endovascular treatments (ET). Methods: Reference populations were manually extracted from the field's main guidelines and randomized clinical trials (RCT). Their characteristics were harmonized in a computerized reference database. We developed a web application whose algorithm identifies the reference populations matching the patient's characteristics. It returns the latter's outcomes in a graphical user interface (GUI), whose design has been driven by real-world practices. Results: Strokecopilot has been released at www.digitalneurology.net. The reference database includes 25 reference populations from 2 guidelines and 15 RCTs. After a request, the reference populations matching the patient characteristics are displayed with a summary and a meta-analysis of their results. The status regarding IVT and ET indications are presented as "in guidelines", "in literature", or "outside literature references". The GUI is updated to provide several levels of explanation. Strokecopilot may be updated as the literature evolves by loading a new version of the reference populations' database. Conclusion: Strokecopilot is a literature-based CDSS, developed to support neurologists in the management of the acute phase of AIS. [ABSTRACT FROM AUTHOR]