NLP and making sense of data in a precision medicine world
Linguamatics
During his January 2015 State of the Union speech, President Obama announced details of his administration’s Precision Medicine Initiative, which promises to accelerate the development of tools and therapies that are customized to individual patients. Precision medicine focuses on disease treatment and prevention and considers the variability in genes, environment, and lifestyle between individual patients.
Precision medicine takes into account healthcare’s relatively minor role in impacting a patient’s overall health and well-being, compared to the larger roles of genetics, health behaviors, and social and environmental factors. The precision medicine approach thus requires that providers have access to a wealth of patient-specific data. Thanks to advancements in genetic testing and new technologies, such as patient portals and remote monitoring devices, a wide variety of patient data is now readily available. Unfortunately, clinicians may have difficulty extracting data that is clinically relevant because much of the information is stored in an unstructured format.
Consider how a physician would glean information from a paper medical chart prior to EMRs. To understand a patient’s complete health status, the doctor would search through pages and pages of notes - obviously a time-consuming and error-prone task.