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We offer a pragmatic model to operationalize responsible, secure, and sustainable healthcare AI, aligning world-class technical excellence with organizational readiness. The framework includes five key pillars - Leadership & Strategy, MLOps…

Computers and Society · Computer Science 2025-10-21 Jimmy Joseph

A multi-arm multi-stage trial is a multi-arm trial which includes interim analyses - analysing the data at certain specified points, generally discontinuing treatments which are concluded to not work and proceeding with the remainder. It is…

Methodology · Statistics 2022-11-14 Martin Law

Researchers have widely used accelerated life tests to determine an optimal inspection plan for lot acceptance. All such plans are proposed by assuming a known relationship between the lifetime characteristic(s) and the accelerating stress…

Computation · Statistics 2026-02-06 Sandip Barui , Shovan Chowdhury

Efficiently allocating treatments with a budget constraint constitutes an important challenge across various domains. In marketing, for example, the use of promotions to target potential customers and boost conversions is limited by the…

Machine Learning · Computer Science 2024-05-06 Toon Vanderschueren , Wouter Verbeke , Felipe Moraes , Hugo Manuel Proença

Investigators often evaluate treatment effects by considering settings in which all individuals are assigned a treatment of interest, assuming that an unlimited number of treatment units are available. However, many real-life treatments are…

Pulmonary drug delivery systems rely on inhalation of drug-laden aerosols produced from aerosol generators such as inhalers, nebulizers etc. On deposition, the drug molecules diffuse in the mucus layer and are also subjected to mucociliary…

Tissues and Organs · Quantitative Biology 2022-01-14 Aranyak Chakravarty , Mahesh V. Panchagnula , Alladi Mohan , Neelesh A. Patankar

Lung cancer is one of the death threatening diseases among human beings. Early and accurate detection of lung cancer can increase the survival rate from lung cancer. Computed Tomography (CT) images are commonly used for detecting the lung…

Machine Learning · Statistics 2019-11-26 Md Rashidul Hasan , Muntasir Al Kabir

We consider a stopping problem and its application to the decision-making process regarding the optimal timing of organ transplantation for individual patients. At each decision period, the patient state is inspected and a decision is made…

Systems and Control · Electrical Eng. & Systems 2026-04-03 Xingyu Ren , Michael C. Fu , Steven I. Marcus

Clinical trials are an instrument for making informed decisions based on evidence from well-designed experiments. Here we consider adaptive designs mainly from the perspective of multi-arm Phase II clinical trials, in which one or more…

Methodology · Statistics 2021-08-31 Elja Arjas , Dario Gasbarra

Hospital readmission has become a critical metric of quality and cost of healthcare. Medicare anticipates that nearly $17 billion is paid out on the 20% of patients who are readmitted within 30 days of discharge. Although several…

Applications · Statistics 2014-03-14 Issac Shams , Saeede Ajorlou , Kai Yang

Decision making problems are typically concerned with maximizing efficiency. In contrast, we address problems where there are multiple stakeholders and a centralized decision maker who is obliged to decide in a fair manner. Different…

Optimization and Control · Mathematics 2022-12-21 Andrea Lodi , Philippe Olivier , Gilles Pesant , Sriram Sankaranarayanan

We present a novel optimal allocation model for perennial plants, in which assimilates are not allocated directly to vegetative or reproductive parts but instead go first to a storage compartment from where they are then optimally…

Populations and Evolution · Quantitative Biology 2013-10-01 Andrii Mironchenko , Jan Kozlowski

Large variability between cell lines brings a difficult optimization problem of drug selection for cancer therapy. Standard approaches use prediction of value for this purpose, corresponding e.g. to expected value of their distribution.…

Quantitative Methods · Quantitative Biology 2022-09-15 Jarek Duda

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

Liver transplant is an essential therapy performed for severe liver diseases. The fact of scarce liver resources makes the organ assigning crucial. Model for End-stage Liver Disease (MELD) score is a widely adopted criterion when making…

Artificial Intelligence · Computer Science 2023-02-21 Sirui Ding , Ruixiang Tang , Daochen Zha , Na Zou , Kai Zhang , Xiaoqian Jiang , Xia Hu

The principle of allocating an equal number of patients to each arm in a randomized controlled trial remains widely believed to be optimal for maximising statistical power. However, this long-held belief only holds true if the treatment…

Methodology · Statistics 2025-10-15 Lukas Pin , Stef Baas , David S. Robertson , Sofía S. Villar

We consider the sequential allocation of $m$ balls (jobs) into $n$ bins (servers) by allowing each ball to choose from some bins sampled uniformly at random. The goal is to maintain a small gap between the maximum load and the average load.…

Discrete Mathematics · Computer Science 2023-08-11 Dimitrios Los , Thomas Sauerwald , John Sylvester

Rising provider turnover results in frequently needing to rematch patients with available providers. However, the rematching process is cumbersome for both patients and health systems, resulting in labor-intensive and ad hoc reassignments.…

Computers and Society · Computer Science 2025-06-13 Naveen Raman , Holly Wiberg

This paper proposes a novel criterion for the allocation of patients in Phase~I dose-escalation clinical trials aiming to find the maximum tolerated dose (MTD). Conventionally, using a model-based approach the next patient is allocated to…

Methodology · Statistics 2018-07-17 Pavel Mozgunov , Thomas Jaki

Accurate lung cancer risk prediction remains challenging due to substantial variability across patient populations and clinical settings -- no single model performs best for all cohorts. To address this, we propose a personalized lung…

Machine Learning · Computer Science 2025-08-27 Chongyu Qu , Allen J. Luna , Thomas Z. Li , Junchao Zhu , Junlin Guo , Juming Xiong , Kim L. Sandler , Bennett A. Landman , Yuankai Huo