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JavaScript for Cancer Prevention through Early Detection


Skin cancer is a serious problem worldwide but luckily treatment in the early stage can lead to recovery. JavaScript together with a machine learning model can help Medical Doctors increase the accuracy of melanoma detection. During the presentation, Karol will show how to use Tensorflow.js, Keras, and React Native to build a solution that can recognize skin moles and detect if they are melanoma or benign mole. He will also show issues that they have faced during development. In summary, the session includes the pros and cons of JavaScript used for machine learning projects.

Karol Przystalski - Data Sceince Dojo
Karol Przystalski

Founder at Codete GmbH, Board Member at Medtransfer

Karol Przystalski obtained a Ph.D. degree in Computer Science in 2015 at the Jagiellonian University in Cracow. He is the CTO and founder of Codete, leading and mentoring teams at Codete. He is working with Fortune 500 companies on data science projects. He has built a research lab for machine learning methods and big data solutions at Codete. Other than that he also gives speeches and training in data science with a focus on applied machine learning in German, Polish, and English. He used to be an O’Reilly trainer as well.

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