In our last blog, we explored the ways predictive analytics expand the use of Electronic Medical Records (EMRs) by using them to forecast trends that affect the health of both individual patients and whole communities. However, use of predictive analytics is only the beginning to gaining insights from the data contained in EMRs.
Cognitive analytics has opened new doors by enabling healthcare providers to use machine learning and natural language processing to further unlock the disease-fighting potentials of EMRs. These advanced insights serve as weapons in the war against cancer.
Why Cognitive Analytics Are Needed
According to IBM, each patient generates 1 million gigabytes of health data, the equivalent of 300 million books. Without the data storage capacity of IBM POWER, healthcare providers struggle to store and process these vast volumes of data.
Not only is the volume of medical data overwhelming, but most doctor’s notes and scans are unstructured within the system. The natural language processing enabled by cognitive analytics draws associations between textual references so conclusions can be drawn. Cognitive analytics also construes images taken from MRIs, colonoscopies, and other tools used to detect potential conditions, like cancerous tumors.