JavaScript beats cancer

Skin cancer is a serious problem worldwide and treatment in the early stage can lead to recovery. JavaScript together with a machine learning model can help medical doctors increase the accuracy in melanoma detection.
During the presentation we show how to use Tensorflow.js, Keras and React Native to build a solution that can recognize skin moles and detect if it's a melanoma or a benign mole. Karol also shows issues that he has faced during the development. As a summary he presents pros and cons of JavaScript used for machine learning projects.

Vorkenntnisse

  • No special knowledge needed

Lernziele

  • Know how to use Tensorflow in JavaScript
  • How not to use machine learning with JS
  • Understand the basics of ML used in medicine

Speaker

 

Karol Przystalski
Karol Przystalski obtained a PhD degree in Computer Science in 2015 at the Jagiellonian University in Cracow. CTO and founder of Codete. Leading and mentoring teams at Codete. Working with Fortune 500 companies on data science projects. Built a research lab for machine learning methods and big data solutions at Codete. Gives speeches and trainings in data science with a focus on applied machine learning.


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