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Title: Analysing gene variants for various clinical characteristics using Machine Learning
In the presentation I’d like to tell a story about recent research we conducted in Invicta R&D. The study was looking to see if it was possible to identify characteristic gene variants for various clinical characteristics of patients undergoing IVF treatment. During the presentation I’m going to discuss in depth the reasons behind our choices of methods, what were the differences between them, what results were expected and what did surprise us. I will share sample of code that was used, bit of theory and a lot of visuals that helped understand the
problem. Don’t worry if you’re not familiar with genetic data – it won’t be necessary to understand
Speaker: Krystian Zielinski
Krystian is a Data Scientist in R&D department at Invicta. Previously he worked in financial crime area, where his own-developed tools helped to prevent frauds. Currently he analizes genetic data searching for correlations with medical data. His tools based on AI provide core functionalities in IVF stimulation process. He is also conducting lectures Wyższa Szkoła Bankowa in Gdańsk related to Methods of Machine Learning.
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