Friday, April 5, 2013

Characterizing Coronary Artery Disease (CAD) in the EHR

Profs Cai and Shaw led a discussion of the the CAD NLP algorithm and demonstrated how the different priors and different ascertainment biases of different clinics could affect the accuracy of the NLP classification. Also discussed counter-intuitive coefficients in the model which may reflect confounding by the treatments for CAD.

rUntitled

NLP

Guergana's team: discussed speed issues.

cTAKES with full UMLS module takes about 150 notes/hour/core. Discussed various architectural tradeoffs.