/UCI_heart_disease_predictor

The following uses a randomforest/XGBoost approaches to predict heart disease from a number of features. These data are available on Kaggle (see ReadMe).

Primary LanguagePython

UCI_heart_disease

The following uses a random forest approach to predict heart disease from a number of features. Additionally, a second approach using XGBoost was applied with similar findings (faster computational time). After gridsearching for both approaches, the predicting modes is on the order of 87% accurate in predicting heart condition. For the randomforest approach the relative feather importance is determined and plotted using the model feature weights.

These data are available on Kaggle (see below). This database contains 76 attributes, but all published experiments refer to using a subset of 14 of them. In particular, the Cleveland database is the only one that has been used by ML researchers to this date. The "goal" field refers to the presence of heart disease in the patient. It is integer valued from 0 (no presence) to 4.

Content

Attribute Information:

  1. age
  2. sex
  3. chest pain type (4 values)
  4. resting blood pressure
  5. serum cholestoral in mg/dl
  6. fasting blood sugar > 120 mg/dl
  7. resting electrocardiographic results (values 0,1,2)
  8. maximum heart rate achieved
  9. exercise induced angina
  10. oldpeak = ST depression induced by exercise relative to rest
  11. the slope of the peak exercise ST segment
  12. number of major vessels (0-3) colored by flourosopy
  13. thal: 3 = normal; 6 = fixed defect; 7 = reversable defect The names and social security numbers of the patients were recently removed from the database, replaced with dummy values. One file has been "processed", that one containing the Cleveland database. All four unprocessed files also exist in this directory.

To see Test Costs (donated by Peter Turney), please see the folder "Costs"

Acknowledgements Creators:

  1. Hungarian Institute of Cardiology. Budapest: Andras Janosi, M.D.
  2. University Hospital, Zurich, Switzerland: William Steinbrunn, M.D.
  3. University Hospital, Basel, Switzerland: Matthias Pfisterer, M.D.
  4. V.A. Medical Center, Long Beach and Cleveland Clinic Foundation: Robert Detrano, M.D., Ph.D.

Donor: David W. Aha (aha '@' ics.uci.edu) (714) 856-8779

Kaggle: https://www.kaggle.com/ronitf/heart-disease-uci/activity