license: apache-2.0 tags: - vision - image-classification datasets: - https://www.kaggle.com/datasets/tawsifurrahman/tuberculosis-tb-chest-xray-dataset widget: - src: https://huggingface.co/Owos/tb-classifier/blob/main/tb-negative.png example_title: Negative - src: https://huggingface.co/Owos/tb-classifier/blob/main/tb-positive.png example_title: Positive metrics: - Accuracy - Precision - Recall
Tuberculosis Classifier
Model description
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.
#Intended uses & limitations
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.
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
How to use
Download the pre-trained model and use it to make inference.
A space has been created for testing (here)[space.com]
Training data
The entire dataset consist of 3500 negative images and 700 positive TB images.
The data was splitted in 80% for training and 20% for validation.
Training procedure Evaluation results