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Phenotyping is the process of distinguishing groups of patients to identify different types of disease progression. A recent trend employs low-rank matrix and tensor factorization methods for their capability of dealing with multi-modal,…

Machine Learning · Computer Science 2025-06-26 Cristian Minoccheri , Sophia Tesic , Kayvan Najarian , Ryan Stidham

Nested nonparametric processes are vectors of random probability measures widely used in the Bayesian literature to model the dependence across distinct, though related, groups of observations. These processes allow a two-level clustering,…

Methodology · Statistics 2024-10-10 Federico Camerlenghi , Riccardo Corradin , Andrea Ongaro

The incorporation of "real-world data" to supplement the analysis of trials and improve decision-making has spurred the development of statistical techniques to account for introduced confounding. Recently, "hybrid" methods have been…

Diffusion models have recently shown considerable potential in solving Bayesian inverse problems when used as priors. However, sampling from the resulting denoising posterior distributions remains a challenge as it involves intractable…

Machine Learning · Statistics 2024-12-25 Badr Moufad , Yazid Janati , Lisa Bedin , Alain Durmus , Randal Douc , Eric Moulines , Jimmy Olsson

Randomized controlled trials are the gold standard for evaluating the efficacy of an intervention. However, there is often a trade-off between selecting the most scientifically relevant primary endpoint versus a less relevant, but more…

Methodology · Statistics 2026-01-12 Jack M. Wolf , Joseph S. Koopmeiners , David M. Vock

Composite endpoints are increasingly used in clinical trials to capture treatment effects across multiple or hierarchically ordered outcomes. Although inference procedures based on win statistics, such as the win ratio, win odds, and net…

Methodology · Statistics 2025-10-28 Xi Fang , Zhiqiang Cao , Fan Li

Major advances have been made regarding the utilization of artificial intelligence in health care. In particular, deep learning approaches have been successfully applied for automated and assisted disease diagnosis and prognosis based on…

Methodology · Statistics 2020-03-24 Max Westphal , Antonia Zapf , Werner Brannath

In comparative studies of progressive diseases, such as randomized controlled trials (RCTs), the mean Change From Baseline (CFB) of a continuous outcome at a pre-specified follow-up time across subjects in the target population is a…

Methodology · Statistics 2024-11-15 Changyu Shen , Menglan Pang , Ling Zhu , Lu Tian

Prediction performance of a risk scoring system needs to be carefully assessed before its adoption in clinical practice. Clinical preventive care often uses risk scores to screen asymptomatic population. The primary clinical interest is to…

Methodology · Statistics 2018-06-22 Yan Yuan , Qian M. Zhou , Bingying Li , Hengrui Cai , Eric J. Chow , Gregory T. Armstrong

Mixed outcome endpoints that combine multiple continuous and discrete components to form co-primary, multiple primary or composite endpoints are often employed as primary outcome measures in clinical trials. There are many advantages to…

Methodology · Statistics 2019-12-12 Martina McMenamin , Jessica K. Barrett , Anna Berglind , James M. S. Wason

As alternatives to the time-to-first-event analysis of composite endpoints, the {\it net benefit} (NB) and the {\it win ratio} (WR) -- which assess treatment effects using prioritized component outcomes based on clinical importance -- have…

Methodology · Statistics 2020-11-24 Roland A. Matsouaka , Adrian Coles

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

The propensity score analysis is one of the most widely used methods for studying the causal treatment effect in observational studies. This paper studies treatment effect estimation with the method of matching weights. This method…

Methodology · Statistics 2011-05-17 Liang Li

Most statistical tests for treatment effects used in randomized clinical trials with survival outcomes are based on the proportional hazards assumption, which often fails in practice. Data from early exploratory studies may provide evidence…

Statistics Theory · Mathematics 2020-05-28 Andrea Arfé , Brian Alexander , Lorenzo Trippa

Accurate and early prediction of a disease allows to plan and improve a patient's quality of future life. During pandemic situations, the medical decision becomes a speed challenge in which physicians have to act fast to diagnose and…

Machine Learning · Computer Science 2022-06-09 Pierluigi Costanzo , Kalia Orphanou

Measuring disease progression in clinical trials for testing novel treatments for multifaceted diseases as Progressive Supranuclear Palsy (PSP), remains challenging. In this study we assess a range of statistical approaches to compare…

Simultaneous tests of superiority and non-inferiority hypotheses on multiple endpoints are often performed in clinical trials to demonstrate that a new treatment is superior over a control on at least one endpoint and non-inferior on the…

Methodology · Statistics 2023-10-02 Wenfeng Chen , Naiqing Zhao , Guoyou Qin , Jie Chen

In oncological clinical trials, overall survival (OS) is the gold-standard endpoint, but long follow-up and treatment switching can delay or dilute detectable effects. Progression-free survival (PFS) often provides earlier evidence and is…

Methodology · Statistics 2025-12-10 Moritz Fabian Danzer , Kaspar Rufibach , Jan Beyersmann , René Schmidt

The analysis of multiple time-to-event outcomes in a randomised controlled clinical trial can be accomplished with exisiting methods. However, depending on the characteristics of the disease under investigation and the circumstances in…

Methodology · Statistics 2026-03-02 Moritz Fabian Danzer , Andreas Faldum , Thorsten Simon , Barbara Hero , Rene Schmidt

A key aspect of patient-focused drug development is identifying and measuring outcomes that are important to patients in clinical trials. Many medical conditions affect multiple symptom domains, and a consensus approach to determine the…

Methodology · Statistics 2025-10-14 David S. Robertson , Thomas Jaki