
A Machine Learning Approach to Diagnosing Lung and Colon Cancer Using a Deep Learning-Based Classification Framework
Category:- Journal; Year:- 2021
Discipline:- Electronics and Communication Engineering Discipline
School:- Science, Engineering & Technology School
Abstract
The field of Medicine and Healthcare has attained revolutionary
advancements in the last forty years. Within this period, the actual reasons
behind numerous diseases were unveiled, novel diagnostic methods were designed,
and new medicines were developed. Even after all these achievements, diseases
like cancer continue to haunt us since we are still vulnerable to them. Cancer
is the second leading cause of death globally; about one in every six people
die suffering from it. Among many types of cancers, the lung and colon variants
are the most common and deadliest ones. Together, they account for more than
25% of all cancer cases. However, identifying the disease at an early stage
significantly improves the chances of survival. Cancer diagnosis can be
automated by using the potential of Artificial Intelligence (AI), which allows
us to assess more cases in less time and cost. With the help of modern Deep
Learning (DL) and Digital Image Processing (DIP) techniques, this paper inscribes
a classification framework to differentiate among five types of lung and colon
tissues (two benign and three malignant) by analyzing their histopathological
images. The acquired results show that the proposed framework can identify
cancer tissues with a maximum of 96.33% accuracy. Implementation of this model
will help medical professionals to develop an automatic and reliable system
capable of identifying various types of lung and colon cancers.