Developement of Stroke Prognosis Predictive Precision Medicine Based on a Digital Twin

Developement of Prognosis Predictive Precision Medicine Based on a Digital Twin Reflecting the Motor Patterns in Stroke Patients

The purpose of this study is to realize customized precision medicine for stroke patients and the visual digitization of patient medical information required in the era of digital transformation.

This study will collect large-scale, high-quality clinical data and daily life exercise pattern data covering the subacute to chronic stages of stroke patients. Based on this, we will use artificial intelligence analysis technology to predict the functional status of stroke patients in the chronic stage after their disability is fixed. We aim to develop the next generation of personalized digital twins by creating a prognostic prediction model.

Inclusion Criteria:

• Adults over 20 years of age with a history of stroke onset between 2018.01.01 to 2023.07.31.
• Patients who exist rehabilitation medical evaluation after stroke onset
• Patients who voluntarily decide to participate in this study

Exclusion Criteria:

• Those who have severe internal diseases such as unstable conditions of the cardiovascular system, digestive system, respiratory system, endocrine system, etc. and are in poor overall condition.
• Those who have impaired ability to consent (MMSE score less than 10 points) and not accompanied by a care-giver.
• In any other cases where the researcher determines that participation in this study is not appropriate.