Use case in production

JavaScript and ML beat cancer

Karol Przystalski

CTO, Codete & Medtransfer

Karol Przystalski obtained a PhD degree in Computer Science in 2015 at the Jagiellonian University in Cracow. He is now the CTO and founder of Codete, where he has built a research lab for machine learning methods and big data solutions, and he leads and mentors teams. Karol has been working with Fortune 500 companies on data science projects. Karol gives speeches and training in data science, focusing on applied machine learning in German, Polish, and English. Before that, he was also an O’Reilly trainer.

Karol Przystalski
Karol Przystalski
Session description

Skin cancer is a severe 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, we show how to use Tensorflow.js, Keras and React Native to build a solution that can recognize skin moles and detect if they are a melanoma or a benign mole. We also show issues that we have faced during development. In summary, we present the pros and cons of JavaScript used for machine learning projects.