Virtual Melanoma Detection

Melanoma is the deadliest form of skin cancer. It is a type of cancer that develops from the pigment-containing cells known as melanocytes-mutate and become cancerous. In this particular mobile application, we will be providing a feature to detect melanoma with the help of Convolutional Neural Netwo

Project Title

Virtual Melanoma Detection

Project Area of Specialization

Artificial Intelligence

Project Summary

Melanoma is the deadliest form of skin cancer. It is a type of cancer that develops from the pigment-containing cells known as melanocytes-mutate and become cancerous. In this particular mobile application, we will be providing a feature to detect melanoma with the help of Convolutional Neural Networks Algorithms, therefore, using the image classification.

Melanoma is a hazardous type of skin cancer that is usually curable if detected early. As the biopsy (diagnosis) of this disease is a bit expensive and time-consuming procedure. Therefore, to tackle this issue we will be developing an android application through which we can detect melanoma through image classification process by using convolutional neural network algorithm (CNN).

There are three similar projects which are mentioned above but we are giving project with some additional features and high level of accuracy, better than previous ones.

Project Objectives

The primary objective of the project is to detect melanoma at its earliest with at least a detection efficiency of 96% and testing efficiency of at least 92%. The focus is to primarily detect melanoma at its earliest.

Project Implementation Method

Phase 1: Development of Melanoma  Detection mobile application using Machine Learning Algorithms.
Phase 2: Assortment of Datasets from enlightening sites like Kaggle and Google Dataset.
Phase 3: Training of model with dataset by utilizing Convolutional Neural Networks (CNN) Algorithm to recognize non-melanoma and melanoma recognition.

Phase 4: Deployment of prepared neural network model in a mobile application.
Phase 5: Installing of Amazon API in the trained model.
Phase 6: Testing and verifying the model’s performance in the mobile application.

Benefits of the Project

The project will overcome the problem of expensive treatments and expensive diagnosis tests that are opted for the diagnosis of melanoma.

It is the main benefit of the project to detect melanoma with least amount of money spend.

Technical Details of Final Deliverable

The technical and deliverable of the proposed project will be consist of the following:

• The proposed MELDET apllication will be utilized in those places where it will be a very difficult to reached the human being to perform cancer detection operation.
• The MELDET application system will be installed in smartphone and it will be be used with any smartphone clear camera which will help in detecting of melanoma detection and this detection system can be easily equipped in pocket. 

Final Deliverable of the Project

Software System

Core Industry

IT

Other Industries

Medical

Core Technology

Artificial Intelligence(AI)

Other Technologies

Others

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

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