mahsan2 / Monkeypox-dataset-2022

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Monkeypox-dataset-2022

The dataset is collected from google as an open source. However, it should not be used for commercial purposes as we do not hold any rights. There is a higher chance that some of that data is not related to the very recent outbreak of monkeypox or chickenpox disease. Therefore, the machine learning model developed from this dataset should not be used to evaluate any real world patient diagnosis. Also, the dataset is not approved by any ethical committee. Therefore, it should not be used to deploy in actual patient diagnosis.

"Monkeypox_08_15_22" is the code file. This is only for educational and research purpose. The result and any findings should not be used in real world patient diagnosis. More ethical analysis, proper justification, more authentic dataset and expert opinion can help to create more relaiable machine learning model.

There were no authentic chickenpox dataset. We have uploaded a small chickenpox dataset which is collected from Centers for Disease Control and Prevention, Here:https://www.cdc.gov/chickenpox/about/photos.html

The dataset is not sufficient and should not be used for any clinical diagnosis.

During the Onset of Monkeypox disease our aim is to develop a image-based dataset that will assist to develop Artificial Intelligence based disease diagnosis model.

Dataset Name Total Images
Monkeypox 43
Monkeypox_augmented 587
Normal 54
Normal_augmented 552
Measles 17
Measles_augmented 286
Total 1915

Data folder such as Monekypox_gray contains gray image of the original images which might help to reduce the time computation during the training.

If you are using this dataset for the experiment then please cite the following paper

  1. Ahsan, M., Uddin, M., Farjana, M., Sakib, A., Momin, K., & Luna, S.. (2022). Image Data collection and implementation of deep learning-based model in detecting Monkeypox disease using modified VGG16. [Paper link] (https://arxiv.org/abs/2206.01862)
  2. Ahsan, M., Uddin, M., & Luna, S.. (2022). Monkeypox Image Data collection. [Paper link] (https://arxiv.org/abs/2206.01774)