The primary outcome of this study is the criterion standard stroke diagnosis. This will be used to estimate the diagnostic test characteristics of a multi-omic biomarker profile in the peripheral whole blood for distinguishing stroke (IS, TIA, SAH, ICH) versus non-stroke in ED patients with acute neurologic symptoms. Secondly, the investigators will estimate the ability of the multi-omic biomarker profile to differentiate between stroke subtypes. A diagnosis of stroke will be defined as clinical syndromes consistent with stroke (i.e., sudden onset neurological deficit) plus imaging confirmation (or symptom resolution and lack of imaging findings in TIA). Finally, the investigators will explore the relationship between the multi-omic profile and time from symptom onset in ischemic stroke patients. Descriptive and inferential statistics will be used to address the aims of the study. Pattern recognition analysis and machine learning will be employed as a systems level approach to determine relevant pathophysiologic pathways associated with diagnosis and symptom onset time.