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Artificial intelligence hastens review for asthma risk

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Susan Millard, MD, FCCP

Susan Millard, MD, FCCP, comments: This article brings mixed emotions. On one hand, using artificial intelligence brings a more thorough evaluation regarding asthma risk. On the other hand, our pediatric pulmonary subspecialty has gotten diluted over the last 3 decades. We used to regularly do arterial puncture, thoracentesis, and chest tube placement procedures. Now a computer might replace another aspect of our job, too? The practice of medicine is an art and that art should not be lost.


 

REPORTING FROM AAAAI/WAO JOINT CONGRESS 2018


Researchers found a high level of agreement between the NLP analysis and the manual review. For breastfeeding, the positive predictive value (PPV) of the NLP was 98% and the negative predictive value (NPV) was 86%. For history of atopic conditions the PPV was at or near 100%, with a NPV of 97% to 99%, depending on the condition.

For family history of atopic conditions, the PPV was 91% to 100%, depending on the condition, and the NPV was 96% to 99%.

“Childhood asthma risk factors identified (an) NLP algorithm using EHR has excellent concordance with chart review,” researchers wrote.

Using an average time per chart, researchers found that it would take 7 hours to complete a manual review for the information presented in the study, compared to 50 minutes for the NLP.

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