Individualized risk assessment of preoperative opioid use by interpretable neural network regression
From MaRDI portal
Publication:2686044
DOI10.1214/22-AOAS1634OpenAlexW4320169862MaRDI QIDQ2686044
Yuming Sun, Chad Brummett, Yi Li, Jian Kang
Publication date: 24 February 2023
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2205.08370
Cites Work
- Unnamed Item
- Unnamed Item
- A selective overview of deep learning
- Nonparametric regression using deep neural networks with ReLU activation function
- On deep learning as a remedy for the curse of dimensionality in nonparametric regression
- Size, power and false discovery rates
- Large-Scale Machine Learning with Stochastic Gradient Descent
- Bayesian Deep Net GLM and GLMM
- Efficient Estimation and Inferences for Varying-Coefficient Models
- Correlation and Large-Scale Simultaneous Significance Testing
- Large-Scale Simultaneous Hypothesis Testing
- Varying Coefficient Regression Models: A Review and New Developments
This page was built for publication: Individualized risk assessment of preoperative opioid use by interpretable neural network regression