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Early Breast-Cancer-Detection

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Inspiration

The whole month of October is celebrated as Breast Cancer awareness month and it is treated as an imported drawback in lack of awareness and in technology to cure breast cancers in women. One of our teammate's family member faced the same issue for years , due to lack of latest technology and availability the treatment got delayed. That inspired us to take up this idea and work the project.

What it does

It helps in early detection of breast cancer in a person using machine learning and deep learning.

How we built it

We have built it using python, sklearn, tensorflow and few regression models in machine learning like decision tree and rain forest algorithm using them comparatively which gives the best accuracy accordingly.

Challenges we ran into:

We faced challenges especially using the dataset and the constant fluctuating accuracy while working it. Major challenge was faced during the plotting of box plots, violet graphs, although it made us learn more about them in depth. Accomplishments that we're proud of

Proud of executing the content that we've learnt as subjects in our education curriculum and actually representing them as projects using latest technology in this huge platform.

What we learned

Learnt about managing time, team management, working under different opinions.Academically, learnt about plotting violet graphs and box plots. Maintaining patience while obtaining the correct accuracy

What's next for Breast Cancer Detection using Machinelearning & Deeplearning

One of the biggest issues for breast cancer diagnosis is getting women to get themselves screened Usings artificial intelligence (AI) to develop personalized outreach strategies for women all around the world, image-based AI comes to the rescue in this case with solutions to help radiologists make the right decisions and faster treatment cause prevention is always better than cure!

About

This was the submission for IBM ZDatathon ( US Edition )

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