Transfer Contrastive Learning for Raman Spectroscopy Skin Cancer Tissue Classification

This dataset was originally collected by Erzina et al.(2020). I have added the dataset to this project while you can also download it from Kaggle, Cells Raman Spectra

Currently, a random dataset was generated for running the baseline code, a simulated dataset generated by GNN which also follows the original distribution will be released after paper has been accepted.

cd src
python ml_baseline.py

This command runs the 6 traditional machine learning models: LogisticRegression, SVC, RandomForestClassifier, DecisionTreeClassifier, KNeighborsClassifier

cd src
python nn_baseline.py

This commands runs the 4 neural network models, including 1 MLP, 1 LSTM, and 2 CNNs

cd src
python train_models.py

If you find this is useful, please cite our paper

@article{wang2024transfer,
  title={Transfer Contrastive Learning for Raman Spectroscopy Skin Cancer Tissue Classification},
  author={Wang, Zhiqiang and Lin, Yanbin and Zhu, Xingquan},
  journal={IEEE Journal of Biomedical and Health Informatics},
  year={2024},
  publisher={IEEE}
}