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README.md
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# Tuberculosis Classifier
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# Model description
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This is a computer vision model that was built with TensorFlow to classify if a given x-ray scan is positive for Tuberculosis or not.
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#Intended uses & limitations
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The model was built to help support low-resourced and short-staffed primary healthcare centers in Nigeria. Particularly, the aim to was created a computer-aided diagnosing tool for Radiologists in these centers.
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The model has not undergone clinical testing and usage is at ueser's own risk.The model has however been tested on real life data images that are positive for tuberculosis
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Download the pre-trained model and use it to make inference.
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A space has been created for testing (here)[space.com]
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The entire dataset consist of 3500 negative images and 700 positive TB images. </br>
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The data was splitted in 80% for training and 20% for validation.
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Training procedure
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Evaluation results
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# Tuberculosis Classifier
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# Model description
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This is a computer vision model that was built with TensorFlow to classify if a given x-ray scan is positive for Tuberculosis or not.
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+
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#Intended uses & limitations
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The model was built to help support low-resourced and short-staffed primary healthcare centers in Nigeria. Particularly, the aim to was created a computer-aided diagnosing tool for Radiologists in these centers.
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The model has not undergone clinical testing and usage is at ueser's own risk.The model has however been tested on real life data images that are positive for tuberculosis
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#How to use
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Download the pre-trained model and use it to make inference.
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A space has been created for testing (here)[space.com]
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#Training data
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The entire dataset consist of 3500 negative images and 700 positive TB images. </br>
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The data was splitted in 80% for training and 20% for validation.
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#Training procedure
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Transfer-learning was employed using InceptionV3 as the pre-trained model. The classes were weighted during training in order to neutralize the imbalanced class.
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Evaluation results
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