Deep Learning Neural Networks to Predict Serious Complications After Bariatric Surgery: Analysis of Scandinavian Obesity Surgery Registry Data.
Dhanisha Jayesh TrivediScott MontgomeryJohan OttossonNäslund ErikStenberg ErikPublished in: JMIR medical informatics (2020)
MLP and CNN showed improved, but limited, ability for predicting the postoperative serious complications after bariatric surgery in the Scandinavian Obesity Surgery Registry data. However, the overfitting issue is still apparent and needs to be overcome by incorporating intra- and perioperative information.
Keyphrases
- neural network
- minimally invasive
- coronary artery bypass
- insulin resistance
- deep learning
- metabolic syndrome
- weight loss
- electronic health record
- patients undergoing
- type diabetes
- weight gain
- high fat diet induced
- big data
- convolutional neural network
- risk factors
- cardiac surgery
- artificial intelligence
- magnetic resonance imaging
- adipose tissue
- percutaneous coronary intervention
- acute kidney injury
- skeletal muscle
- healthcare
- data analysis
- physical activity
- social media
- atrial fibrillation