Anemia Estimation for Patients Using a ML Model

Project Code :TCPGPY397

Objective

The main objective of this project is to create an Effective Detection system for Anemia among individuals and taking necessary treatment in order to get rid from anemia.

Abstract

Computer-aided illness diagnosis is less expensive, saves time, is more accurate, and removes the need for additional personnel in medical decision making. Many nutrition surveys indicate that about a quarter of the world's population is anaemic. As a result, there is a pressing need to create an effective machine learning regressor capable of properly detecting anaemia. The goal is to find out which individual classifier or group of classifier combinations obtain the highest accuracy in Red blood cell categorization for anaemia detection. We used Lasso and Ridge regressions to detect and estimate the anaemia. However the classifier Ridge performs better achieves an accuracy higher than the Lasso regression. Hence to achieve maximum accuracy in medical decision making, a better and powerful algorithm should be used. The outcomes of this algorithms decides whether the patient is infected with anaemia or not. The proposed version generates a better response to the inputs to confirm the disease.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

SOFTWARE SPECIFICATIONS:

  • Technology: Machine Learning, Application.
  • Libraries: Pandas, Numpy, Sklearn.
  • Version: Python 3.6+
  • Server-side scripts: HTML, CSS, JS
  • Frame works: Flask
  • IDE: Pycharm
  • Database: MySql

HARDWARE SPECIFICATIONS:

  • RAM: 8GB, 64-bit os.
  • Processor: I3/Intel processor
  • Hard Disk Capacity: 128 GB +

Learning Outcomes

  • About Python.
  • About PyCharm.
  • About Pandas.
  • About Numpy.
  • About HTML.
  • About CSS.
  • About Database.
  • About Machine Learning.
  • About Artificial Intelligent.
  • About how to use the libraries.
  • Virtualization.
  • About how to create the registration table in sql.
  • About model choosing.
  • About prediction outcomes for the Anemia Patients
  • About how to generate the predictions with python code.
    • Project Development Skills:
    • Problem analyzing skills.
    • Problem solving skills.
    • Creativity and imaginary skills.
    • Programming skills.
    • Deployment.
    • Testing skills.
    • Debugging skills.
    • Project presentation skills.
    • Thesis writing skills.

Demo Video

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