Related papers: Bi-level Multi-criteria Optimization for Risk-info…
This paper presents a novel algorithmic study with extensive numerical experiments of distributionally robust multistage convex optimization (DR-MCO). Following the previous work on dual dynamic programming (DDP) algorithmic framework for…
Robo-advisors (RAs) are automated portfolio management systems that complement traditional financial advisors by offering lower fees and smaller initial investment requirements. While most existing RAs rely on static, one-period allocation…
Magnetic resonance imaging (MRI) is a non-invasive medical imaging technique offering high-resolution 3D images and valuable insights into human tissue conditions. Even at present, the refinement of denoising methods for MRI remains a…
Combinatorial Optimization (CO) encompasses a wide range of problems that arise in many real-world scenarios. While significant progress has been made in developing learning-based methods for specialized CO problems, a unified model with a…
The paper considers two different designs; a two-arm superiority cluster randomised controlled trial (RCT) with a continuous outcome, and a twoarm superiority cluster RCT with a binary outcome. From a Bayesian perspective, for the analysis…
In a treatment plan optimization problem for radiotherapy, a clinically acceptable plan is usually generated by an optimization process with weighting factors or reference doses adjusted for organs. Recent discoveries indicate that…
Hospital readmissions remain a challenge for healthcare systems, especially among patients with chronic conditions such as diabetes. Unplanned readmissions within 30 days are costly, strain hospital resources, and can indicate poor care…
It is a big challenge to develop efficient models for identifying personalized drug targets (PDTs) from high-dimensional personalized genomic profile of individual patients. Recent structural network control principles have introduced a new…
An important goal in cancer research is the survival prognosis of a patient based on a minimal panel of genomic and molecular markers such as genes or proteins. Purely data-driven models without any biological knowledge can produce…
Medical imaging has revolutionized diagnosis, yet unnecessary procedures are rising, exposing patients to radiation and stress, limiting equitable access, and straining healthcare systems. The American College of Radiology Appropriateness…
Randomized Controlled Trials (RCTs) are the gold standard for comparing the effectiveness of a new treatment to the current one (the control). Most RCTs allocate the patients to the treatment group and the control group by uniform…
In this paper, we revisit the multistage spectral risk minimization models proposed by Philpott et al.~\cite{PdF13} and Guigues and R\"omisch \cite{GuR12} but with some new focuses. We consider a situation where the decision maker's (DM's)…
Given the prominence of targeted therapy and immunotherapy in cancer treatment, it becomes imperative to consider heterogeneity in patients' responses to treatments, which contributes greatly to the widely used proportional hazard…
Introduction: Increasing interest in real-world evidence has fueled the development of study designs incorporating real-world data (RWD). Using the Causal Roadmap, we specify three designs to evaluate the difference in risk of major adverse…
Dose-finding clinical trials in oncology aim to estimate the maximum tolerated dose (MTD), based on safety traditionally obtained from the clinician's perspective. While the collection of patient-reported outcomes (PROs) has been advocated…
Radiology report generation requires advanced medical image analysis, effective temporal reasoning, and accurate text generation. Although recent innovations, particularly multimodal large language models, have shown improved performance,…
Objective: Radiation therapy treatment planning is a time-consuming, iterative process with potentially high inter-planner variability. Fully automated treatment planning processes could reduce a planner's active treatment planning time and…
The conventional more-is-better dose selection paradigm, which targets the maximum tolerated dose (MTD), is not suitable for the development of targeted therapies and immunotherapies as the efficacy of these novel therapies may not increase…
Motivation: Multi-omics integration can improve cancer subtyping, but modality informativeness and noise vary across cancer types and patients. Existing graph-based methods optimize modality weights jointly with the classification objective…
With the intensiffcation of population aging and increasing burden of chronic diseases, the demand for vital signs monitoring is becoming increasingly urgent. A key challenge facing current non-contact detection technologies using…