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Addiction is a major societal issue leading to billions in healthcare losses per year. Policy makers often introduce ad hoc quantity limits-limits on the consumption or possession of a substance-something which current economic models of…

Theoretical Economics · Economics 2024-07-25 Eric Gao

The goal of this article is to investigate how human participants allocate their limited time to decisions with different properties. We report the results of two behavioral experiments. In each trial of the experiments, the participant…

Neurons and Cognition · Quantitative Biology 2016-07-20 Arash Khodadadi , Pegah Fakhari , Jerome R. Busemeyer

This paper develops a data-driven, constraint-based optimization framework for a complex industrial job shop scheduling problem variant in pharmaceutical manufacturing. The formulation captures fixed routings and designated machines,…

The long-term efficacy of targeted therapeutics for cancer treatment can be significantly limited by the type of therapy and development of drug resistance, inter alia. Experimental studies indicate that the factors enhancing acquisition of…

Tissues and Organs · Quantitative Biology 2021-02-16 Joseph Malinzi , Kevin Bosire Basita , Sara Padidar , Henry A. Adeola

Recent clinical trials have shown that the adaptive drug therapy can be more efficient than a standard MTD-based policy in treatment of cancer patients. The adaptive therapy paradigm is not based on a preset schedule; instead, the doses are…

Quantitative Methods · Quantitative Biology 2020-08-06 Mark Gluzman , Jacob G. Scott , Alexander Vladimirsky

There is wide interest in studying how the distribution of a continuous response changes with a predictor. We are motivated by environmental applications in which the predictor is the dose of an exposure and the response is a health…

Methodology · Statistics 2018-05-10 Antonio Canale , Daniele Durante , David Dunson

Optimization is an important module of modern machine learning applications. Tremendous efforts have been made to accelerate optimization algorithms. A common formulation is achieving a lower loss at a given time. This enables a…

Machine Learning · Computer Science 2025-05-29 Zhonglin Xie , Yiman Fong , Haoran Yuan , Zaiwen Wen

Dynamic treatment regimes are of growing interest across the clinical sciences as these regimes provide one way to operationalize and thus inform sequential personalized clinical decision making. A dynamic treatment regime is a sequence of…

Methodology · Statistics 2013-11-27 Eric B. Laber , Min Qian , Dan J. Lizotte , William E. Pelham , Susan A. Murphy

Quality control in industrial processes is increasingly making use of prior scientific knowledge, often encoded in physical models that require numerical approximation. Statistical prediction, and subsequent optimization, is key to ensuring…

Other Statistics · Statistics 2018-10-23 Antony Overstall , David Woods , Kieran Martin

In a Phase II dose-finding study with a placebo control, a new drug with several dose levels is compared with a placebo to test for the effectiveness of the new drug. The main focus of such studies often lies in the characterization of the…

Methodology · Statistics 2020-07-14 Saswati Saha , Werner Brannath

Precision medicine is currently a topic of great interest in clinical and intervention science. One way to formalize precision medicine is through a treatment regime, which is a sequence of decision rules, one per stage of clinical…

Methodology · Statistics 2016-06-07 Yichi Zhang , Eric B. Laber , Anastasios Tsiatis , Marie Davidian

Studies often report estimates of the average treatment effect. While the ATE summarizes the effect of a treatment on average, it does not provide any information about the effect of treatment within any individual. A treatment strategy…

Methodology · Statistics 2025-06-13 Nicholas T. Williams , Katherine L. Hoffman Iván Díaz , Kara E. Rudolph

This paper studies optimal scheduling and resource allocation under allowable over-scheduling. Formulating an optimisation problem where over-scheduling is embedded, we derive an optimal solution that can be implemented by means of a new…

Optimization and Control · Mathematics 2022-04-04 Wei Ren , Eleftherios Vlahakis , Nikolaos Athanasopoulos , Raphael M. Jungers

Early phase, personalized dose-finding trials for combination therapies seek to identify patient-specific optimal biological dose (OBD) combinations, which are defined as safe dose combinations which maximize therapeutic benefit for a…

Methodology · Statistics 2024-04-18 James Willard , Shirin Golchi , Erica EM Moodie

Exploratory cancer drug studies test multiple tumor cell lines against multiple candidate drugs. The goal in each paired (cell line, drug) experiment is to map out the dose-response curve of the cell line as the dose level of the drug…

Machine Learning · Statistics 2021-03-23 Wesley Tansey , Christopher Tosh , David M. Blei

In the era of targeted therapy, there has been increasing concern about the development of oncology drugs based on the "more is better" paradigm, developed decades ago for chemotherapy. Recently, the US Food and Drug Administration (FDA)…

Methodology · Statistics 2022-09-07 Beibei Guo , Ying Yuan

In this article, we propose a phase I-II design in two stages for the combination of molecularly targeted therapies. The design is motivated by a published case study that combines a MEK and a PIK3CA inhibitors; a setting in which higher…

Methodology · Statistics 2025-05-21 José L. Jiménez , Mourad Tighiouart

A treatment regime formalizes personalized medicine as a function from individual patient characteristics to a recommended treatment. A high-quality treatment regime can improve patient outcomes while reducing cost, resource consumption,…

Methodology · Statistics 2015-04-30 Yichi Zhang , Eric B. Laber , Anastasios Tsiatis , Marie Davidian

Medication adherence is a problem of widespread concern in clinical care. Poor adherence is a particular problem for patients with chronic diseases requiring long-term medication because poor adherence can result in less successful…

Methodology · Statistics 2021-04-26 Kristen B. Hunter , Mark E. Glickman , Luis F. Campos

We consider repeated measurement designs when a residual or carry-over effect may be present in at most one later period. Since assuming an additive model may be unrealistic for some applications and leads to biased estimation of treatment…

Statistics Theory · Mathematics 2014-11-20 R. A. Bailey , P. Druilhet