karensylee / ICS435_Final_MyCopy

AIDS Clinical Trials Group Study 175 Dataset from https://archive.ics.uci.edu/dataset/890/aids+clinical+trials+group+study+175

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My ICS435 project is predicting AIDS Using Machine Learning in HIV Clinical Trials.

  • The dataset consists of healthcare statistics collected from patients diagnosed with acquired immunodeficiency syndrome (AIDS), initially published in 1996 by Hammer et al. see AIDS_Classification.csv in the data folder.

  • The ICS435_FProject.pdf is the written submission.

  • Three types of models were trained through Google Colab: Neural Network, Random Forest, and Support Vector Machines. The code for each model are the jupyter notebooks:

    • ICS435_FProject_NN.ipynb ;
    • ICS435_FProject_RF.ipynb ;
    • ICS435_FProject_SVM.ipynb
  • The best trained models are saved in the models folder.

Hammer, S. M., Katzenstein, D. A., Hughes, M. D., Gundacker, H., Schooley, R. T., Haubrich, R. H., ... & Merigan, T. C. (1996). A trial comparing nucleoside monotherapy with combination therapy in HIV-infected adults with CD4 cell counts from 200 to 500 per cubic millimeter. New England Journal of Medicine, 335(15), 1081-1090.

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AIDS Clinical Trials Group Study 175 Dataset from https://archive.ics.uci.edu/dataset/890/aids+clinical+trials+group+study+175


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