Sequenced Treatment Alternatives to Relieve Depression

By E. Lin, Pochu Ho. 2018

27 citations recorded by the source corpus.

Subfields: Pharmacology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Pharmacology

1. Michael R. Kosorok
2. Shamim Nemati
3. Donglin Zeng
4. Chao Yu
5. Jiming Liu
6. Yuanjia Wang
7. Ying Liu
8. Ying‐Qi Zhao

Citations in the corpus

• Reinforcement Learning in Healthcare: A Survey (2019, methodology): “Using data from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial [194], which is a sequenced four-stage randomized clinical trial of patients with MDD, Pineau et al.”
• Robust Hybrid Learning for Estimating Personalized Dynamic Treatment Regimens (2016, methodology): “…are useful in treating many complex chronic disorders such as substance dependence, attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), major depressive disorder (MDD), and schizophrenia (Schneider et al., 2003; Rush et al., 2004, 2006; Oslin, 2005; Jones, 2010).”