Mutation Detection in Cancer Gene using Machine Learning

Cancer has been identified as a serious issue which causes numerous deaths every year all around the globe. Late prognosis and diagnosis of cancer disease is one of the major causes of deaths. This proposal will lead to the solution of mutation detection problem in cancer gene

Project Title

Mutation Detection in Cancer Gene using Machine Learning

Project Area of Specialization

Artificial Intelligence

Project Summary

Cancer has been identified as a serious issue which causes numerous deaths every year all around the globe. Late prognosis and diagnosis of cancer disease is one of the major causes of deaths. This proposal will lead to the solution of mutation detection problem in cancer gene which may help in diagnosing the cancer in early stages. Mutation is the disturbance in gene sequence and increasing number of studies showed that mutated genes are crucial for cancer growth. This project aims the detection of mutation in the gene sequence whether it is mutated or not. To detect mutation in gene sequence, several techniques and models of machine learning might be considered in this project.

Project Objectives

The objective of the project is to design a system for mutation detection in cancer genes. By the means of mutation detection, cancer can be diagnosis in early stages. The early prognosis of the cancer may helpful in reducing the death ratio due to cancer and facilitate to cure it.

Project Implementation Method

To detect mutation in oncogene sequence, several techniques and models of machine learning might be considered such as Random Forest, SVM, Logistic Regression or RNN to achieve better detection accuracy. All of these techniques will be implement in python using FDD(Feature Driven Development) agile framework. The prototype of this project will be developed using different designing tools such as Figma or Adobe Illustrator.

Benefits of the Project

Following are some benefits of this project:

1. Mutation in cancer genes will be detected.
2. Due to mutation detection, it will become easy to diagnose cancer at the initial stages.
3. It might be helpful in the easy treatment of cancer.
4. A number of lives can be saved using this system.

Technical Details of Final Deliverable

We are using several machine learning tools and techniques to achieve our goals. Machine learning is an application of artificial intelligence in which machines learn by themselves.

Machine learning models such as SVM, Logistic regression and others might be used in developing this system.

SVM  (support vector machine) is a machine learning model. It works on clustering techniques and could be useful in this project.

Logistic regression is also a machine learning model. It works on the probability of any event and returns a value in boolean format.

Flask is the python web framework used for back-end web development.

Final Deliverable of the Project

Hardware System

Core Industry

Medical

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People, Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com