Cargando…
Prediction of Stroke Outcome Using Natural Language Processing-Based Machine Learning of Radiology Report of Brain MRI
Brain magnetic resonance imaging (MRI) is useful for predicting the outcome of patients with acute ischemic stroke (AIS). Although deep learning (DL) using brain MRI with certain image biomarkers has shown satisfactory results in predicting poor outcomes, no study has assessed the usefulness of natu...
Autores principales: | Heo, Tak Sung, Kim, Yu Seop, Choi, Jeong Myeong, Jeong, Yeong Seok, Seo, Soo Young, Lee, Jun Ho, Jeon, Jin Pyeong, Kim, Chulho |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7766032/ https://www.ncbi.nlm.nih.gov/pubmed/33339385 http://dx.doi.org/10.3390/jpm10040286 |
Ejemplares similares
-
Deep learning based prediction of prognosis in nonmetastatic clear cell renal cell carcinoma
por: Byun, Seok-Soo, et al.
Publicado: (2021) -
Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke
por: Kim, Chulho, et al.
Publicado: (2019) -
Prediction of Hemorrhagic Transformation after Ischemic Stroke Using Machine Learning
por: Choi, Jeong-Myeong, et al.
Publicado: (2021) -
Influence of Anesthesia Type on Outcomes after Endovascular Treatment in Acute Ischemic Stroke: Meta-Analysis
por: Kim, Chulho, et al.
Publicado: (2019) -
Monitoring of Delayed Cerebral Ischemia in Patients with Subarachnoid Hemorrhage via Near-Infrared Spectroscopy
por: Park, Jeong Jin, et al.
Publicado: (2020)