README.md

---
license: mit
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Actinic keratoses
          '1': Basal cell carcinoma
          '2': Benign keratosis-like lesions
          '3': Chickenpox
          '4': Cowpox
          '5': Dermatofibroma
          '6': HFMD
          '7': Healthy
          '8': Measles
          '9': Melanocytic nevi
          '10': Melanoma
          '11': Monkeypox
          '12': Squamous cell carcinoma
          '13': Vascular lesions
  splits:
  - name: train
    num_bytes: 11781822388.236
    num_examples: 29322
  - name: validation
    num_bytes: 1129580056.38
    num_examples: 3660
  - name: test
    num_bytes: 1166877801.52
    num_examples: 3674
  download_size: 9960809758
  dataset_size: 14078280246.136002
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
---

# Skin Lesions Dataset
A dataset for 14 types of skin lesions classification consisted of merging [HAM10000(2019)](https://www.kaggle.com/datasets/andrewmvd/isic-2019) and [MSLDv2.0](https://www.kaggle.com/datasets/joydippaul/mpox-skin-lesion-dataset-version-20-msld-v20)

The dataset consisted of 14 categories:
- Actinic keratoses
- Basal cell carcinoma
- Benign keratosis-like-lesions
- Chickenpox
- Cowpox
- Dermatofibroma
- Healthy
- HFMD
- Measles
- Melanocytic nevi
- Melanoma
- Monkeypox
- Squamous cell carcinoma
- Vascular lesions

## Download the dataset locally
Follow [Kaggle API guide](https://www.kaggle.com/docs/api) to get started
```bash
kaggle datasets download -d ahmedxc4/skin-ds
```


Citation for the original datasets

### MSLDv2.0
```
@article{Nafisa2023,
title={A Web-based Mpox Skin Lesion Detection System Using State-of-the-art Deep Learning Models Considering Racial Diversity},
author={Ali, Shams Nafisa and Ahmed, Md. Tazuddin and Jahan, Tasnim and Paul, Joydip and Sani, S. M. Sakeef and Noor, Nawshaba and Asma, Anzirun Nahar and Hasan, Taufiq},
journal={arXiv preprint arXiv:2306.14169},
year={2023}
}
```

### HAM10000 (2019)
```
BCN_20000 Dataset: (c) Department of Dermatology, Hospital Clínic de Barcelona

HAM10000 Dataset: (c) by ViDIR Group, Department of Dermatology, Medical University of Vienna; https://doi.org/10.1038/sdata.2018.161

MSK Dataset: (c) Anonymous; https://arxiv.org/abs/1710.05006; https://arxiv.org/abs/1902.03368
```