Decode Human Immune System for Blood Disease Detection using Machine Learning Algorithms

Authors

  • Ria Vijay Nagaonkar
  • Suraj Rajaram Jare
  • Rishi Vinod Pandey
  • Suhasini Parvatikar

Abstract

Quick and accurate medical diagnosis are crucial for the successful treatment of diseases. Using machine learning algorithm and based on laboratory blood test result, we have built a model to predict hematology diseases. It is a predictive model which uses various symptoms causing the disease and a few blood parameters to detect the disease. Blood analysis is an essential indicator for many diseases. It contains several parameters which are sign for various specific blood diseases. For predicting the disease according to blood analysis, symptoms that leads to identifying the disease precisely should be recognized. Our model uses machine learning which is the field responsible for building models for predicting the output based on previous data. Accuracy of the machine learning algorithm is based on quality of data collected for learning process.

Keywords: Disease, Symptoms, Blood Parameters, technology, human immune system, algorithm.

Cite this Article: Ria Vijay Nagaonkar, Suraj Rajaram Jare, Rishi Vinod Pandey, Suhasini Parvatikar. Decode Human Immune System for Blood Disease Detection using Machine Learning Algorithms. Journal of Advancements in Robotics. 2020; 7(2): 9–14p.

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Published

2020-08-06

Issue

Vol. 7 No. 2 (2020)

Section

Research Articles

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