Establishment of a Value-Added Center for Stroke Clinical Big Data and Study on Intelligent Medical Healthcare Models( I )

Stroke is the fourth leading cause of death in USA, the third in Taiwan and the first in mainland China. Stroke is also the most common cause of disability in the world. The management of stroke usually depends on prevention rather than treatment. Once stroke attacks, there is more or less poststroke handicap. At present, the standard treatment for acute ischemic stroke is intravenous rt-PA thrombolysis treated within 3 hours after stroke onset and intra-arterial mechanical thrombectomy within 3-6 hours. These acute stroke stage treatment demands early recognition of stroke symptoms and urgent hospital arrival. However, even though intra-venous and intra-arterial thrombolysis has demonstrated good evidence of stroke improvement. Only around 10-20% patients can arrive earlier and receive such kinds of treatment. In the medical decision of stroke management strategy, three stages are important including primary prevention, acute stage treatment and secondary prevention. Research team members of this project are relatedt to clinical medicine, clinical nursing, information management, intelligent decision analysis, industrial design, data science research fields. The research team consists of clinical doctors and nurses of Chang Gung Memorial Hospital, teachers of Chang Gung University, and industrial experts. This project will integrate clinical big data for stroke from Chang Gung Medical Hospitcals and healthcare information from other institutes to develop a Value-Added Center of Stroke Clinical Big Data. It will further desgin intelligent decision models using data science technologies for improving medical quality. We hope that such a center will act as an important center for developing stroke clinical big data research. This project consists six sub-projects as follows: Sub-project I: Information government and privacy protecton for the stroke clinical big data platform. Sub-project II: Image analysis for the patient with high stroke risk. Sub-project III: Study on identification of high risk factors based on big data technologies. Sub-project IV: Intelligent decision analysis for stroke medicine. Sub-project V: Multiple criteria decision making for emergency stroke medical services. Sub-project VI: Study on stroke patient rehabilitation therapy services and usability analysis.

Project ID:PF10507-1767
External Project ID:MOST105-2632-H182-001