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This is a Python- based implementation of various (at least 10) Research Studies/ Articles/ proposals already published on the task of heart disease prediction using Machine Learning and accomplishment the same results.

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IN DEV!

This is a Python- based implementation of various (at least 10) Research Studies/ Articles/ proposals already published on the task of heart disease prediction using Machine Learning and accomplishment the same results. The contributors to this project are:

  1. Akshay Raina
  2. Shubam Sumbria
  3. Vishal

To reuse the code file/s or visual resources, please cite us at-

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  1. Details of the Papers/ Articles Implemented
  2. Traversing the Repo

Details of the Papers/ Articles Implemented:

  1. Heart Disease Prediction using Multilayer Perceptron Algorithm
    • Cite at: Kirmani MM. Heart disease prediction using multilayer perceptron algorithm. International Journal of Advanced Research in Computer Science. 2017 May 15;8(5)
    • Methodology: MM Kirmani used the Multilayer Perceptron Model with hidden layers and back- propagation to classify an instance into diseased or fit. He also used the 10- fold cross validation with an intention to overcome imbalance of fitting.
    • Dataset Used: Cleveland from the UCI ML Repository.
  2. HDPM: An Effective Heart Disease Prediction Model for a Clinical Decision Support System
    • Cite at: Fitriyani NL, Syafrudin M, Alfian G, Rhee J. HDPM: An Effective Heart Disease Prediction Model for a Clinical Decision Support System. IEEE Access. 2020 Jul 20;8:133034-50.
    • Methodology:

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This is a Python- based implementation of various (at least 10) Research Studies/ Articles/ proposals already published on the task of heart disease prediction using Machine Learning and accomplishment the same results.

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