Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications.

Paul ThottakkaraTezcan Ozrazgat-BaslantiBradley B HupfParisa RashidiPanos PardalosPetar MomcilovicAzra Bihorac

Published in: PloS one (2016)

Generalized additive models and support vector machines had good performance as risk prediction model for postoperative sepsis and AKI. Feature extraction using principal component analysis improved the predictive performance of all models.

Keyphrases

machine learning
acute kidney injury
big data
artificial intelligence
patients undergoing
intensive care unit
deep learning
electronic health record
septic shock
data analysis