Abstract WP74: An Automated, Electronic Health Record-based Algorithm To Classify Ischemic Stroke Etiology
Introduction: Determining acute ischemic stroke (AIS) etiology is central to secondary stroke
prevention, but can be diagnostically challenging. We built a stroke etiology classification …
prevention, but can be diagnostically challenging. We built a stroke etiology classification …
StrokeClassifier: ischemic stroke etiology classification by ensemble consensus modeling using electronic health records
Determining acute ischemic stroke (AIS) etiology is fundamental to secondary stroke
prevention efforts but can be diagnostically challenging. We trained and validated an …
prevention efforts but can be diagnostically challenging. We trained and validated an …
Machine learning-based prediction of stroke in emergency departments
Background: Stroke misdiagnosis, associated with poor outcomes, is estimated to occur in
9% of all stroke patients. Objectives: We hypothesized that machine learning (ML) could …
9% of all stroke patients. Objectives: We hypothesized that machine learning (ML) could …
Predicting Ischemic Stroke In Emergency Departments: Development And Validation Of Machine Learning Models
V Abedi, D Misra, D Chaudhary, V Avula, CM Schirmer… - Stroke, 2022 - Am Heart Assoc
Background: Stroke misdiagnosis is estimated to occur in 9% of all stroke patients and is
associated with poor outcomes. We hypothesized that machine learning (ML) could be used …
associated with poor outcomes. We hypothesized that machine learning (ML) could be used …
P287 Use of machine learning to determine stroke severity of patients diagnosed with stroke in claims data
E Kogan, K Twyman, J Heap, D Milentijevic… - European Heart …, 2018 - academic.oup.com
Background: The National Institutes of Health Stroke Scale (NIHSS) scores are often
recorded as free text in the neurologist's diagnosis reports, and not readily available in …
recorded as free text in the neurologist's diagnosis reports, and not readily available in …
Use of machine learning to determine stroke severity of patients diagnosed with stroke in integrated claims-medical records dataset
E Kogan, K Twyman, J Heap, D Milentijevic, JH Lin… - Circulation, 2017 - Am Heart Assoc
Introduction: The National Institutes of Health Stroke Scale (NIHSS) scores are often
recorded in a form of free text in the neurologist's diagnosis reports and this information is …
recorded in a form of free text in the neurologist's diagnosis reports and this information is …
Abstract WP315: An Electronic Health Record Phenotype of Ischemic Stroke Using Non-Claims Clinical Data and Machine Learning
BR Kummer, JM Luna, CC Esenwa, H Salmasian… - Stroke, 2017 - Am Heart Assoc
Introduction: Real-time identification of patients with acute ischemic stroke (AIS) in the
electronic health record (EHR) can enhance care delivery systems, clinical decision support …
electronic health record (EHR) can enhance care delivery systems, clinical decision support …
Comparative analysis, applications, and interpretation of electronic health record-based stroke phenotyping methods
Background Accurate identification of acute ischemic stroke (AIS) patient cohorts is essential
for a wide range of clinical investigations. Automated phenotyping methods that leverage …
for a wide range of clinical investigations. Automated phenotyping methods that leverage …
Towards automated incidence rate reporting: Leveraging machine learning technologies to assist stroke adjudication in a large-scale epidemiological study
Introduction: Epidemiological studies utilizing administrative databases typically use
International Classification of Diseases (ICD) codes to identify stroke cases and estimate …
International Classification of Diseases (ICD) codes to identify stroke cases and estimate …
Abstract P259: Using Natural Language Processing and Machine Learning to Identify Incident Stroke From Electronic Health Records
Background: The focus of most existing phenotyping algorithms based on electronic health
record (EHR) data has been to accurately identify cases and non-cases of specific diseases …
record (EHR) data has been to accurately identify cases and non-cases of specific diseases …