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Case Studies

Reproductive Science Center of the Bay Area: Machine Learning for Yield Prediction

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"Many clinical practices don't have data scientists in their staff, they have to use tools like Driverless AI to be able to extract valuable insights from their clinical data. What Driverless AI is doing for us is to just make it easier because it will do all the model creation and sampling. And make it more robust and fast. In old times, 2 years ago, 3 years ago, it all goes by published papers but now because we have data in our hands, we can make the same decisions based on our data. With the data, we can more accurate faster decisions, so it's a better way of doing science in clinical healthcare."

Oleksii Barash
Research Director

Use Cases

Precision Medicine

Yield Prediction

Overview of the Challenge

Evaluate all the available factors for reproductive science and use machine learning to make sense of the collected data.