NLP-based Extraction of Social Determinants of Health in Patients Admitted with Spontaneous Intracranial Hemorrhage (P11-2.005)

E Zelt, A Al-Dhoon, U Topaloglu, A Sarwal - Neurology, 2024 - AAN Enterprises
Objective: To determine the effectiveness of extraction of Social Determinants of Health in
ICH patient notes. Background: Social Determinants of Health (SDOH) have been a focus of …

The Association of Social Determinants of Health on Functional Outcome After Intracerebral Hemorrhage (P10-2.001)

T McVeigh, P Rist, A Mallick, S Mora, C Kourkoulis… - Neurology, 2024 - AAN Enterprises
Objective: NA Background: It remains unknown which social determinants of health (SDOH)
are impactful or when disparities begin to emerge in intracerebral hemorrhage (ICH). This …

[HTML][HTML] Extraction of Radiological Characteristics From Free-Text Imaging Reports Using Natural Language Processing Among Patients With Ischemic and …

E Hsu, AT Bako, T Potter, AP Pan, GW Britz, J Tannous… - JMIR AI, 2023 - ai.jmir.org
Background Neuroimaging is the gold-standard diagnostic modality for all patients
suspected of stroke. However, the unstructured nature of imaging reports remains a major …

[HTML][HTML] Automated Extraction of Stroke Severity from Unstructured Electronic Health Records using Natural Language Processing

M Fernandes, MB Westover, AB Singhal, SF Zafar - medRxiv, 2024 - ncbi.nlm.nih.gov
BACKGROUND: Multi-center electronic health records (EHR) can support quality
improvement initiatives and comparative effectiveness research in stroke care. However …

Automated Extraction of Stroke Severity from Unstructured Electronic Health Records using Natural Language Processing

M Bento Fernandes, B Westover, AB Singhal, SF Zafar - medRxiv, 2024 - medrxiv.org
BACKGROUND: Multi-center electronic health records (EHR) can support quality
improvement initiatives and comparative effectiveness research in stroke care. However …

Automated Extraction of Stroke Severity from Unstructured Electronic Health Records using Natural Language Processing

B Westover, AB Singhal, SF Zafar - 2024 - europepmc.org
BACKGROUND: Multi-center electronic health records (EHR) can support quality
improvement initiatives and comparative effectiveness research in stroke care. However …

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 …

[HTML][HTML] Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke

C Kim, V Zhu, J Obeid, L Lenert - PloS one, 2019 - journals.plos.org
Background and purpose This project assessed performance of natural language
processing (NLP) and machine learning (ML) algorithms for classification of brain MRI …

Psychological Outcome after Hemorrhagic Stroke is related to Functional Status (P6-6.006)

S Ecker, A Lord, L Gurin, K Ishida, K Melmed, J Torres… - 2022 - AAN Enterprises
Objective: To evaluate the relationship between psychological outcome after hemorrhagic
stroke and functional status. Background: To identify opportunities to improve morbidity after …

[HTML][HTML] Classification of neurologic outcomes from medical notes using natural language processing

MB Fernandes, N Valizadeh, HS Alabsi… - Expert systems with …, 2023 - Elsevier
Neurologic disability level at hospital discharge is an important outcome in many clinical
research studies. Outside of clinical trials, neurologic outcomes must typically be extracted …