activity
20102026
most cited- and -Learning Methods for Estimating Optimal Dynamic Treatment Regimes

183 citations · 348 across the 27 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

stat.ML2019

High dimensional precision medicine from patient-derived xenografts

Naim U. Rashid, Daniel J. Luckett, Jingxiang Chen +8

The complexity of human cancer often results in significant heterogeneity in response to treatment. Precision medicine offers potential to improve patient outcomes by leveraging th…

stat.ME2019★ 2 cited

Sample Size Calculations for SMARTs

Eric J. Rose, Eric B. Laber, Marie Davidian +3

Sequential Multiple Assignment Randomized Trials (SMARTs) are considered the gold standard for estimation and evaluation of treatment regimes. SMARTs are typically sized to ensure…

stat.ML2019

Global forensic geolocation with deep neural networks

Neal S. Grantham, Brian J. Reich, Eric B. Laber +6

An important problem in forensic analyses is identifying the provenance of materials at a crime scene, such as biological material on a piece of clothing. This procedure, known as…

stat.ME2019★ 1 cited

Note on Thompson sampling for large decision problems

Tao Hu, Eric B. Laber, Zhen Li +2

There is increasing interest in using streaming data to inform decision making across a wide range of application domains including mobile health, food safety, security, and resour…

stat.ME2019★ 78 cited

Efficient augmentation and relaxation learning for individualized treatment rules using observational data

Ying-Qi Zhao, Eric B. Laber, Yang Ning +2

Individualized treatment rules aim to identify if, when, which, and to whom treatment should be applied. A globally aging population, rising healthcare costs, and increased access…