ArticleJournal of machine learning research : JMLR2016
Multi-Objective Markov Decision Processes for Data-Driven Decision Support.
Article in Journal of machine learning research : JMLR, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- Influencing factors and spatiotemporal heterogeneity of land-use carbon emissions in China's urban agglomerations.Scientific reports · 2025Article
- A Bayesian multivariate hierarchical model for developing a treatment benefit index using mixed types of outcomes.BMC medical research methodology · 2024Article
- Fusing Individualized Treatment Rules Using Secondary Outcomes.Proceedings of machine learning research · 2024Article
- Multiobjective tree-based reinforcement learning for estimating tolerant dynamic treatment regimes.Biometrics · 2024Article
- Improving Individualized Treatment Decisions: A Bayesian Multivariate Hierarchical Model for Developing a Treatment Benefit Index using Mixed Types of Outcomes.medRxiv : the preprint server for health sciences · 2024Article
- Optimal Personalized Treatment Selection with Multivariate Outcome Measures in a Multiple Treatment Case.Communications in statistics: Simulation and computation · 2023Article
- Quantiles based personalized treatment selection for multivariate outcomes and multiple treatments.Statistics in medicine · 2022Article
- Knowledge graph-based recommendation framework identifies drivers of resistance in EGFR mutant non-small cell lung cancer.Nature communications · 2022Article
- Multi-Response Based Personalized Treatment Selection with Data from Crossover Designs for Multiple Treatments.Communications in statistics: Simulation and computation · 2022Article
- Step-adjusted tree-based reinforcement learning for evaluating nested dynamic treatment regimes using test-and-treat observational data.Statistics in medicine · 2021Article
- Estimation and Optimization of Composite Outcomes.Journal of machine learning research : JMLR · 2021Article
- Near-optimal Individualized Treatment Recommendations.Journal of machine learning research : JMLR · 2020Article
- Bayesian Nonparametric Policy Search with Application to Periodontal Recall Intervals.Journal of the American Statistical Association · 2020Article
- Precision Medicine.Annual review of statistics and its application · 2019Article
- An Optimal Policy for Patient Laboratory Tests in Intensive Care Units.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2019Article
- Identifying optimal dosage regimes under safety constraints: An application to long term opioid treatment of chronic pain.Statistics in medicine · 2018Article
- Incorporating Patient Preferences into Estimation of Optimal Individualized Treatment Rules.Biometrics · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
We present new methodology based on Multi-Objective Markov Decision Processes for developing sequential decision support systems from data. Our approach uses sequential decision-making data to provide support that is useful to many different decision-makers, each with different, potentially time-varying preference. To accomplish this, we develop an extension of fitted-
Indexed as
Identifiers
28018133PMC5179144What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.