8 Steps for Building Health Predictive Models using Open Source Technologies – Vik Kumar, M.D.

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Building health predictive models is a critical application of data science in healthcare. In this article, Vik Kumar, M.D. outlines eight steps for building health predictive models using open source technologies.

Discover how to collect and preprocess data, define outcomes and predictors, select appropriate modeling techniques, and validate the model. Learn how to use open source technologies such as Python, R, and TensorFlow to make predictions and generate insights. Explore real-world examples of health predictive models and their applications in healthcare.

Join physician turned data scientist, Vik Kumar, M.D., as he prepares builds, evaluates and refines a predictive healthcare model in Python.

Speaker Bio

Vik Kumar, MD is a physician-turned-data scientist. He completed his Masters in Computational Science and Engineering at Georgia Tech in 2015 and has since worked as a Data Scientist at both healthcare and non-healthcare companies.

Dr. Kumar currently works for Digital Envoy in Norcross, GA. He is the author of Healthcare Analytics Made Simple, published by Packt in 2018.

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