The primary objective of this study is to develop and validate claims-based algorithms to identify intracerebral hemorrhage >1 cm in diameter, ensuring differentiation from amyloid-related imaging abnormality-microhemorrhage and hemosiderin deposit (ARIA-H; microhemorrhage, superficial siderosis) in participants with Alzheimer's disease (AD) using claims data in the United States (US) with linkage to electronic health records (EHRs), and to estimate the positive predictive values (PPVs) of the algorithms. The secondary objective of the study is to validate claims-based algorithms to identify new-onset seizures in participants with AD using US claims data with linkage to EHRs and to estimate the PPVs of the algorithms.
Inclusion Criteria:
Exclusion Criteria:
esi_medinfo@eisai.com+1-888-274-2378
The Role of Advanced Electroencephalographic Data as Marker of Pathology and Prognosis in Primary Dementias
Digital Solutions for Predicting the Biological Mechanisms of Alzheimer's Disease Through the Analysis of Risk Factors
AI Models for Cerebral Aneurysms Segmentation, Detection and Stability Prediction
Using Artificial Intelligence to Detect Early Signs of Alzheimer's Disease in People With Memory Concerns
Evaluating the Efficacy of Artificial Intelligence-based Computer Aided Diagnosis Software That Assists in Determining Whether or Not to Conduct Amyloid PET for the Diagnosis of Alzheimer's Disease by Predicting Amyloid PET Positivity in Mild Cognitive Impairment Patients
Algorithm Development Through AI for the Triage of Stroke Patients in the Ambulance With EEG
Health Technology Assessment of Diagnostic Approaches in Alzheimer's Disease
Exploratory Clinical Study and Validation of Blood Biomarkers for Alzheimer's Disease