Shadab Hussain

Shadab Hussain
Liverpool John Moores University | LJMU · School of Computing and Mathematical Sciences

Master of Science

About

4
Publications
5,273
Reads
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3
Citations
Additional affiliations
September 2018 - present
Liverpool John Moores University
Position
  • Master's Student
Education
July 2013 - June 2017
United Institute of Technology
Field of study
  • Computer Science Engineering

Publications

Publications (4)
Conference Paper
Full-text available
In the last few years, with the increased population, the most critical component of human life is healthcare. Compare to other deadly diseases, heart disease is one of the most lethal diseases, affecting the lives of millions of people worldwide. It is very important to detect heart disease must early so the loss of lives can be prevented. The ava...
Conference Paper
Full-text available
In the present paper, four different interpolation methods, namely Newton-Gregory Forward, Newton-Gregory Backward, Lagrange and Newton divided difference, are used for solving the real life problem.
Conference Paper
The present paper discusses a new algorithm to find the root of non-linear transcendental functions. It is found that Regula-Falsi method always gives guaranteed result but slow convergence. However, interpolation based method does not give guaranteed result but faster than Regula-Falsi method. Therefore, the present paper used these two thoughts a...
Conference Paper
The present paper describes a new algorithm to find a root of non-linear transcendental equations. It is found that the Regula-Falsi method always gives guaranteed results but slow convergence. However, the Newton–Raphson method does not give guaranteed result but faster than Regula-Falsi method. Therefore, the present paper used these two ideas an...

Projects

Project (1)
Project
With an estimated 2.3 million new cases in 2020, female breast cancer has become the leading cause of global cancer incidence by surpassing lung cancer and accounts for 11.7 percent of overall cancer cases with 685,000 deaths. It’s the fifth leading cause of cancer mortality across the world, accounting for one out of every four cancer cases and one out of every six cancer death. Detection procedures are currently very time-consuming, and the results obtained are not very quick, so we need technologies that are more reliable, faster, and efficient. A classical machine can perform one operation at one time, which means it takes too long to solve a problem that can be solved by quantum computers. The current research aims to use Quantum Machine Learning (QML) and Quanvolutional Neural Networks for breast cancer classification using histopathological images and will compare its efficiency with existing ML and DL techniques.