A Novel Machine Learning Based Screening Method for High-Risk Covid-19 Patients Based on Simple Blood Exams

Project Code :TCMAPY505

Objective

The main objective of this project is to detect the risk severity of the covid patient based on their blood samples by using machine learning algorithms.

Abstract

Based on easily analysed circulatory blood indicators, this article provides a prediction model for possibly identifying high-risk COVID-19 infected individuals. These findings may be used to develop effective and efficient treatment plans for high-risk patients, as well as periodic monitoring for low-risk patients, easing the hospital flow of patients. They can also be used to analyse hospital bed usage. The current machine learning-based methods result in a higher accuracy in classifying COVID-19 infected patients as high-risk patients who require hospitalisation and low-risk patients who may not require hospitalisation.

KEYWORDSCOVID-19, treatment, machine learning, hospitalization...

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

Block Diagram

Specifications

HARDWARE SPECIFICATIONS:

  • Processor: I3/Intel
  • Processor RAM: 4GB (min)
  • Hard Disk: 128 GB
  • Key Board: Standard Windows Keyboard
  • Mouse: Two or Three Button Mouse
  • Monitor: Any

SOFTWARE SPECIFICATIONS:

  • Operating System: Windows 7+
  • Server-side Script: Python 3.6+
  • IDE: PyCharm
  • Libraries Used: Pandas, Numpy.
  • Frame Work: Streamlit

Learning Outcomes

  • About Python.
  • About PyCharm.
  • About Pandas.
  • About Numpy.
  • About Streamlit.
  • About Framework
  • About Machine Learning.
  • About Artificial Intelligence.
  • About how to use the libraries.
  • Classification.
  • About model choosing.
  • About Stream-lit Framework
  • 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.

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