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--- |
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license: cc-by-4.0 |
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datasets: |
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- mauro-nievoff/MultiCaRe_Dataset |
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language: |
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- en |
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pipeline_tag: image-classification |
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tags: |
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- medical |
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--- |
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# MultiCaReClassifier for Medical Image Classification |
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The **MultiCaReClassifier** is a model ensemble used for multilabel medical image classification. It includes classes such as: |
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- image_type: 'radiology', 'pathology', 'endoscopy', 'ophthalmic_imaging', 'medical_photograph', 'electrography', 'chart'. |
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- image_subtype: 'ultrasound', 'x_ray', 'ct', 'mri', 'h&e', 'immunostaining', 'fundus_photograph', 'ekg', 'eeg', etc. |
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- radiology_region: 'thorax', 'head', 'abdomen', 'upper_limb', 'lower_limb', etc. |
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- radiology_view: 'frontal', 'sagittal', 'axial', 'oblique', etc. |
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1. Clone this repo: |
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``` |
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!git clone https://huggingface.co/mauro-nievoff/MultiCaReClassifier |
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``` |
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2. Change the directory: |
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``` |
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%cd /content/MultiCaReClassifier |
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``` |
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3. Import the MultiCaReClassifier class: |
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``` |
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from MultiCaReClassifier.pipeline import * |
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``` |
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4. Get the predictions for a given image folder: |
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``` |
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predictions = MultiCaReClassifier(image_folder = '/content/img') |
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predictions.data.head() |
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``` |
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- **Model Training by:** Facundo Roffet |
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- **Data Curation and Postprocessing by:** Mauro Nievas Offidani |
