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Machine Learning in healthcare can be applied to digitally prognose (predictive diagnosis) using the risk factors of a disease. ML can detect patterns of certain diseases with patient electronic health records and report anomalies to the pattern. ML Diagnostic applications are increasingly being used to supplement clinicians’ decisions, using data lakes to condensify millions of observations of diseases. To instantiate the power of machine learning as a medical prognostic tool, I examined its use in cervical cancer to classify one’s risk of having it, using risk factors, using a publicly available Cervical Cancer Risk Classification Data Set. In this tutorial, you'll see Using Machine Learning to Prognose Cervical Cancer: A Step by Step Guide