ArticleScientific reports2021
Prediction of ambulatory outcome in patients with corona radiata infarction using deep learning.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 24 citations in OpenAlex.
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- Added Value of One-Month Clinical Data in Predicting Chronic-Stage Motor Function After Ischemic Stroke.Journal of clinical medicine · 2026Article
- Deep Learning Algorithm to Determine the Presence of Rectal Cancer from Transrectal Ultrasound Images.Life (Basel, Switzerland) · 2025Article
- Multiple imputation integrated to machine learning: predicting post-stroke recovery of ambulation after intensive inpatient rehabilitation.Scientific reports · 2024Article
- Multi-modality multi-task model for mRS prediction using diffusion-weighted resonance imaging.Scientific reports · 2024Article
- Convolutional neural network algorithm trained on lumbar spine radiographs to predict outcomes of transforaminal epidural steroid injection for lumbosacral radicular pain from spinal stenosis.Scientific reports · 2024Article
- Deep Learning Algorithm Trained on Oblique Cervical Radiographs to Predict Outcomes of Transforaminal Epidural Steroid Injection for Pain from Cervical Foraminal Stenosis.Pain and therapy · 2024Article
- Identification of L5 vertebra on lumbar spine radiographs using deep learning.The Journal of international medical research · 2024Article
- Localization of early infarction on non-contrast CT images in acute ischemic stroke with deep learning approach.Scientific reports · 2023Article
- The Use of Artificial Intelligence to Predict the Prognosis of Patients Undergoing Central Nervous System Rehabilitation: A Narrative Review.Healthcare (Basel, Switzerland) · 2023Review
- Deep Learning Algorithm Trained on Cervical Magnetic Resonance Imaging to Predict Outcomes of Transforaminal Epidural Steroid Injection for Radicular Pain from Cervical Foraminal Stenosis.Journal of pain research · 2023Article
- Use of Machine Learning in Stroke Rehabilitation: A Narrative Review.Brain & NeuroRehabilitation · 2022Review
- Deep Learning Algorithm Trained on Brain Magnetic Resonance Images and Clinical Data to Predict Motor Outcomes of Patients With Corona Radiata Infarct.Frontiers in neuroscience · 2021Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Deep learning (DL) is an advanced machine learning approach used in diverse areas such as bioinformatics, image analysis, and natural language processing. Here, using brain magnetic resonance imaging (MRI) data obtained at early stages of infarcts, we attempted to develop a convolutional neural network (CNN) to predict the ambulatory outcome of corona radiata infarction at six months after onset. We retrospectively recruited 221 patients with corona radiata infarcts. A favorable outcome of ambulatory function was defined as a functional ambulation category (FAC) score of ≥ 4 (able to walk without a guardian's assistance), and a poor outcome of ambulatory function was defined as an FAC score of < 4. We used a CNN algorithm. Of the included subjects, 69.7% (n = 154) were assigned randomly to the training set and the remaining 30.3% (n = 67) were assigned to the validation set to measure the model performance. The area under the curve was 0.751 (95% CI 0.649-0.852) for the prediction of ambulatory function with the validation dataset using the CNN model. We demonstrated that a CNN model trained using brain MRIs captured at an early stage after corona radiata infarction could be helpful in predicting long-term ambulatory outcomes.
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