Stroke Classification
3 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Stroke Classification
| Trend | Dataset | Best Model | Paper | Code | Compare |
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kaggle stroke Prediction competition
Latest papers with no code
Predicting recovery following stroke: deep learning, multimodal data and feature selection using explainable AI
The highest classification accuracy 0. 854 was observed when 8 regions-of-interest was extracted from each MRI scan and combined with lesion size, initial severity and recovery time in a 2D Residual Neural Network. Our findings demonstrate how imaging and tabular data can be combined for high post-stroke classification accuracy, even when the dataset is small in machine learning terms.
Automatic Stroke Classification of Tabla Accompaniment in Hindustani Vocal Concert Audio
The tabla is a unique percussion instrument due to the combined harmonic and percussive nature of its timbre, and the contrasting harmonic frequency ranges of its two drums.
Radiologist-level stroke classification on non-contrast CT scans with Deep U-Net
Segmentation of ischemic stroke and intracranial hemorrhage on computed tomography is essential for investigation and treatment of stroke.
Stroke lesion detection using convolutional neural networks
Stroke is an injury that affects the brain tissue, mainly caused by changes in the blood supply to a particular region of the brain.
