Can we learn individual-level treatment policies from clinical data?

[1]  Alan M. Zaslavsky,et al.  Machine learning methods for developing precision treatment rules with observational data. , 2019, Behaviour research and therapy.

[2]  Rae Woong Park,et al.  Characterizing treatment pathways at scale using the OHDSI network , 2016, Proceedings of the National Academy of Sciences.

[3]  Mark J. van der Laan,et al.  Cross-Validated Targeted Minimum-Loss-Based Estimation , 2011 .

[4]  Robert Fletcher,et al.  Systematic Review: The Relationship between Clinical Experience and Quality of Health Care , 2005, Annals of Internal Medicine.

[5]  Alexander Peysakhovich,et al.  Observational Data for Heterogeneous Treatment Effects with Application to Recommender Systems , 2019, EC.

[6]  Shiro Tanaka,et al.  Analysis of case-cohort designs with binary outcomes: Improving efficiency using whole-cohort auxiliary information , 2017, Statistical methods in medical research.

[7]  Ewout Steyerberg,et al.  Personalized evidence based medicine: predictive approaches to heterogeneous treatment effects , 2018, British Medical Journal.

[8]  Ewout W Steyerberg,et al.  Models with interactions overestimated heterogeneity of treatment effects and were prone to treatment mistargeting. , 2019, Journal of clinical epidemiology.

[9]  M. J. van der Laan,et al.  STATISTICAL INFERENCE FOR THE MEAN OUTCOME UNDER A POSSIBLY NON-UNIQUE OPTIMAL TREATMENT STRATEGY. , 2016, Annals of statistics.

[10]  L. Lind,et al.  The Precision HYpertenSIon Care (PHYSIC) study: a double-blind, randomized, repeated cross-over study , 2018, Upsala journal of medical sciences.

[11]  Mark J van der Laan,et al.  Evaluating the impact of treating the optimal subgroup , 2016, Statistical methods in medical research.

[12]  Mark J van der Laan,et al.  Targeted Learning of the Mean Outcome under an Optimal Dynamic Treatment Rule , 2015, Journal of causal inference.

[13]  Ronald C. Kessler,et al.  Sample Size Requirements for Multivariate Models to Predict Between-Patient Differences in Best Treatments of Major Depressive Disorder , 2019, Clinical Psychological Science.

[14]  Fredrik D. Johansson,et al.  Learning Weighted Representations for Generalization Across Designs , 2018, 1802.08598.

[15]  S. Senn.  Mastering variation: variance components and personalised medicine , 2015, Statistics in medicine.

[16]  Stefan Wager,et al.  Estimation and Inference of Heterogeneous Treatment Effects using Random Forests , 2015, Journal of the American Statistical Association.

[17]  S. Murphy,et al.  PERFORMANCE GUARANTEES FOR INDIVIDUALIZED TREATMENT RULES. , 2011, Annals of statistics.