AI Allows Computers to " Read " EHR Records and Make Predictions

I have blogged previously about utilizing machine learning software andnatural language processing (NLP) to extract meaning from EHR records (see, for example:What Is the Significance of the Roche Acquisition of Flatiron?). This approach to healthcare research is starting to bear fruit (see:Machines Learn To Read Hospital Records, Will Doctor's Handwriting Be Next?). Below is an excerpt from a recent article describing artificial intelligence (AI) and EHR records:Patient records are unruly; they consist of numbers, images, and text....As a result of the jumble of data types and formats, data mining to identify predictive analytics initially require a careful selection of variables of interest which are abstracted from medical records and put in a machine-readable form....A paper in Nature Partner Journals/Digital Medicine provides a proof of concept that the bottleneck has been removed. The researchers were given access to 216,221 de-identified hospital records from two major teaching hospitals, nearly 46 billion individual pieces of data.Algorithms for natural language processing were unleashed on the data automating the conversion of unruly hospital records into a machine-readable format.The resulting data were then utilized to develop predictive models of patient mortality, readmissions, length of stay and discharge diagnosis. The study was retrospective, but because hospital records are time-stamped, the data could be ordered along a timeline to simulate real-ti...
Source: Lab Soft News - Category: Laboratory Medicine Authors: Tags: Electronic Health Record (EHR) Healthcare Information Technology Healthcare Innovations Medical Ethics Medical Research Source Type: blogs