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Diagnosis of Breast Cancer using Deep learning

Nguyen, Chanh (2019)

 
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Chanh thesis.pdf (3.290Mt)
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Nguyen, Chanh
2019
All rights reserved. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-201904165069
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This project covers the fundamentals knowledge of artificial intelligence in general and deep learning in particular, covers the vision of technologies developed in the future.
Artificial intelligent becomes more necessary in human daily life, smartphone, laptop, computer, self-driven cars, smart houses, virtual assistant. On the other hands, they can be quite useful when added to the healthcare system and impacts, managing a large amount of clinical data, diagnosis of certain types of diseases. With the common goal is to make human life better, longer and more joyful.

Cancer is the cause of death of many people around the globe. One of the main reasons for cancer rate increases is simply because of human longevity, climate changes, overpopulation, environment impacts, alcohol consuming, people are getting more and more overweight and obese, changes in lifestyles raises the risk of developing a certain type of cancers. Women are detected positive with breast cancer at a younger age, one of the main reasons is women start to have fewer babies later, breastfeed less.

The motivation of this project is based on my curiosity about learning new technology in the computer field. Artificial intelligence has been and will be a powerful companion of computer scientists in the world. This project was working on the spring of 2019 as the thesis project for my bachelor’s degree in engineering. The goal of this project is to bring the newest technologies to improve human healthcare and well-being. Apply deep learning into the healthcare system, help people can diagnose cancer more accurate and at sooner stages to increase the chance of surviving and enjoy the happiness after treatments. The outcome goal will build a convolutional neural network model to predict the presence of a cancer tumor in scanned specimens.
 
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