Machine Learning to Predict Acute Kidney Injury

The widescale adoption of electronic health record (EHR) technology has led to an unprecedented accumulation of medical data, such that petabytes of patient information are now easily accessible to computer systems. Data have inherent value, as evidenced by the astounding success of technology companies that rely primarily on the exchange of data to generate profit.1 However, data science in health care has been stunted compared with other industries. This is due in no small part to limitations in accessing health data due to concerns regarding privacy, questions over data ownership, and uncertainties around applicability.