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Opioids are the preferred medications for the treatment of pain in the intensive care unit. While undertreatment leads to unrelieved pain and poor clinical outcomes, excessive use of opioids puts patients at risk of experiencing multiple…

Machine Learning · Computer Science 2019-04-26 Daniel Lopez-Martinez , Patrick Eschenfeldt , Sassan Ostvar , Myles Ingram , Chin Hur , Rosalind Picard

Longitudinal electronic health record (EHR) data are often left-censored, making diagnosis records incomplete and unreliable for determining disease onset. In contrast, outpatient prescriptions form renewal-based trajectories that provide a…

Machine Learning · Computer Science 2026-03-02 Pavlin G. Poličar , Dalibor Stanimirović , Blaž Zupan

The current body of research on developing optimal treatment strategies often places emphasis on intention-to-treat analyses, which fail to take into account the compliance behavior of individuals. Methods based on instrumental variables…

Methodology · Statistics 2024-02-21 Cuong T. Pham , Kevin G. Lynch , James R. McKay , Ashkan Ertefaie

Period-prevalent cohorts are often used for their cost-saving potential in epidemiological studies of survival outcomes. Under this design, prevalent patients allow for evaluations of long-term survival outcomes without the need for long…

Methodology · Statistics 2024-10-28 Nicholas Hartman

This thesis conducts an observational study into whether diuretics should be administered to ICU patients with sepsis when length of stay in the ICU and 30-day post-hospital mortality are considered. The central contribution of the thesis…

Applications · Statistics 2014-08-29 Daniele Ramazzotti

There has been significant attention given to developing data-driven methods for tailoring patient care based on individual patient characteristics. Dynamic treatment regimes formalize this through a sequence of decision rules that map…

Methodology · Statistics 2022-02-22 Eric J. Rose , Erica E. M. Moodie , Susan Shortreed

Pharmaco-epidemiology (PE) is the study of uses and effects of drugs in well defined populations. As medico-administrative databases cover a large part of the population, they have become very interesting to carry PE studies. Such databases…

Artificial Intelligence · Computer Science 2017-09-12 Yann Dauxais , Thomas Guyet , David Gross-Amblard , André Happe

The Predictive Approaches to Treatment Effect Heterogeneity statement focused on baseline risk as a robust predictor of treatment effect and provided guidance on risk-based assessment of treatment effect heterogeneity in the RCT setting.…

When devising a course of treatment for a patient, doctors often have little quantitative evidence on which to base their decisions, beyond their medical education and published clinical trials. Stanford Health Care alone has millions of…

Although increasingly used as a data resource for assembling cohorts, electronic health records (EHRs) pose many analytic challenges. In particular, a patient's health status influences when and what data are recorded, generating sampling…

Methodology · Statistics 2020-04-28 Yifei Sun , Charles E. McCulloch , Kieren A. Marr , Chiung-Yu Huang

Estimating heterogeneous treatment effects is an important problem across many domains. In order to accurately estimate such treatment effects, one typically relies on data from observational studies or randomized experiments. Currently,…

Machine Learning · Statistics 2022-02-28 Tobias Hatt , Jeroen Berrevoets , Alicia Curth , Stefan Feuerriegel , Mihaela van der Schaar

Electronic medical records (EMR) contain longitudinal information about patients that can be used to analyze outcomes. Typically, studies on EMR data have worked with established variables that have already been acknowledged to be…

Machine Learning · Computer Science 2017-11-30 Prithwish Chakraborty , Vishrawas Gopalakrishnan , Sharon M. H. Alford , Faisal Farooq

We propose a new method in indefinite-horizon settings for estimating optimal dynamic treatment regimes for time-to-event outcomes. This method allows patients to have different numbers of treatment stages and is constructed using…

Methodology · Statistics 2025-01-31 Jane She , Matthew Egberg , Michael R. Kosorok

Hematotoxicity, drug-induced damage to the blood-forming system, is a frequent side effect of cytotoxic chemotherapy and poses a significant challenge in clinical practice due to its high inter-patient variability and limited…

Machine Learning · Computer Science 2025-05-28 Marie Steinacker , Yuri Kheifetz , Markus Scholz

Chronic kidney disease (CKD) is a gradual loss of renal function over time, and it increases the risk of mortality, decreased quality of life, as well as serious complications. The prevalence of CKD has been increasing in the last couple of…

Machine Learning · Computer Science 2020-11-18 Jinghe Zhang , Kamran Kowsari , Mehdi Boukhechba , James Harrison , Jennifer Lobo , Laura Barnes

In order for clinicians to manage disease progression and make effective decisions about drug dosage, treatment regimens or scheduling follow up appointments, it is necessary to be able to identify both short and long-term trends in…

Quantitative Methods · Quantitative Biology 2016-12-06 Norman Poh , Simon Bull , Santosh Tirunagari , Nicholas Cole , Simon de Lusignan

The cyclical and heterogeneous nature of many substance use disorders highlights the need to adapt the type or the dose of treatment to accommodate the specific and changing needs of individuals. The Adaptive Treatment for Alcohol and…

Methodology · Statistics 2020-05-22 William J. Artman , Ashkan Ertefaie , Kevin G. Lynch , James R. McKay , Brent A. Johnson

In many clinical trials studying neurodegenerative diseases such as Parkinson's disease (PD), multiple longitudinal outcomes are collected to fully explore the multidimensional impairment caused by this disease. If the outcomes deteriorate…

Applications · Statistics 2017-05-18 Jue Wang , Sheng Luo , Liang Li

One of the most common ways researchers compare survival outcomes across treatments when confounding is present is using Cox regression. This model is limited by its underlying assumption of proportional hazards; in some cases, substantial…

Applications · Statistics 2021-02-02 Elizabeth A. Handorf , Marc Smaldone , Sujana Movva , Nandita Mitra

A dynamic treatment regime is a sequence of decision rules in which each decision rule recommends treatment based on features of patient medical history such as past treatments and outcomes. Existing methods for estimating optimal dynamic…

Methodology · Statistics 2015-05-22 Kristin A. Linn , Eric B. Laber , Leonard A. Stefanski