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Breast Cancer Phase Detection

Description

Currently a product prototype for breast cancer lesion detection which predicts and assesses the presence and current stage of cancer lesion based on histopathological reports supplied as inputs to the machine. The machine has the ability to improve its prediction accuracy based on its past records.

It involved application of various specialized Machine Learning and Deep Learning algorithms in Python language entirely, The model was trained on a large authentic data-set to achieve more than 89% accuracy.

It won the 'Best Project Award' under IEEE CS India Council SAC at IEEE Computer Society India Symposium 2018 competing some of the best teams from other top-notch national engineering colleges in the country.

  • Supported by IEEE Computer Society
  • Winners at Technergize 2018 at IEEE CSIS 2018
  • Web - Based Application

Summary

  • The model accepts the histopathological reports of the user as input.
  • Run the trained model on the data provided
  • Computation time may vary from seconds to a few minutes
  • Output is the status and phase of cancer present in the tissue of the image provided

Poster

According to Apollo Hostipals there are more than 1 million cases of breast cancer in women per year in India. Breast cancer is also possible in men, although the chances are low. ProjectPoster

Aim

The project aims to revolutionize cancer treatment throughout the globe and to remove the ambiguity in decision making. This product can act as a confirmatory step which can be used by patients, doctors as well as medical institutions. This can drastically decrease the rate of deaths happening across the globe due to the deadly disease by making the system more efficient and transparent.

Tech

Machine learning and Deep neural network algorithms such as ConvNets, DenseNets, etc. The entire development has been done in Python.

Dataset is available here.

Installation

Not Available Now

Team

Name Connect With Us Or Drop A Mail
Shrutina Agarwal LinkedIn shrutina.agarwal10@gmail.com
Gitesh Jain LinkedIn giteshjain844@gmail.com
Tuhin Das LinkedIn tuhin.loves.federer@gmail.com
Amitrajit Bose LinkedIn amitrajitbose@gmail.com
Sivangi Tandon LinkedIn sivangitandon@gmail.com

Contribute

Want to contribute? Great! 😍 Drop us a message at the contact details provided above.