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In the query-commit problem we are given a graph where edges have distinct probabilities of existing. It is possible to query the edges of the graph, and if the queried edge exists then its endpoints are irrevocably matched. The goal is to…

Data Structures and Algorithms · Computer Science 2011-10-06 Marco Molinaro , R. Ravi

Patients whose transfer to the Intensive Care Unit (ICU) is unplanned are prone to higher mortality rates than those who were admitted directly to the ICU. Recent advances in machine learning to predict patient deterioration have introduced…

Machine Learning · Computer Science 2021-01-26 Julien Grand-Clement , Carri W. Chan , Vineet Goyal , Gabriel Escobar

The morphometry of a kidney tumor revealed by contrast-enhanced Computed Tomography (CT) imaging is an important factor in clinical decision making surrounding the lesion's diagnosis and treatment. Quantitative study of the relationship…

Motivated by the real-world problem of international kidney exchange (IKEP), recent literature introduced a generalized transferable utility matching game featuring a partition of the vertex set of a graph into players, and analyzed its…

Computer Science and Game Theory · Computer Science 2026-02-24 Gergely Csáji , Tamás Király , Zsuzsa Mészáros-Karkus

Cardiovascular-Kidney-Metabolic (CKM) syndrome represents a growing public health crisis, yet the subclinical heterogeneity of its component systems remains underexplored. Early detection of physiological deviation is critical for…

Balancing fairness and efficiency in resource allocation is a classical economic and computational problem. The price of fairness measures the worst-case loss of economic efficiency when using an inefficient but fair allocation rule; for…

Computer Science and Game Theory · Computer Science 2017-09-11 Duncan C. McElfresh , John P. Dickerson

Five year post-transplant survival rate is an important indicator on quality of care delivered by kidney transplant centers in the United States. To provide a fair assessment of each transplant center, an effect that represents the…

Applications · Statistics 2017-03-13 Lanfeng Pan , Yehua Li , Kevin He , Yanming Li , Yi Li

Medical non-adherence increasingly is recognized as a major medical health problem. Approximately 50% of patients do not take their medications as prescribed and such poor adherence has been shown to result in complications, death, and…

Human-Computer Interaction · Computer Science 2017-08-10 Anna Iurchenko

We introduce Disease Knowledge Transfer (DKT), a novel technique for transferring biomarker information between related neurodegenerative diseases. DKT infers robust multimodal biomarker trajectories in rare neurodegenerative diseases even…

Kidney cancer is a global health concern, and accurate assessment of patient frailty is crucial for optimizing surgical outcomes. This paper introduces AI Age Discrepancy, a novel metric derived from machine learning analysis of…

Recent shifts in global health priorities have positioned Population Health Management (PHM) as a central area of focus. However, optimizing PHM strategies presents several challenges: managing high-dimensional patient covariates, tracking…

Optimization and Control · Mathematics 2026-04-10 Daniel Adelman , Alba V Olivares-Nadal , Miaolan Xie

This paper considers a half-duplex scenario where an interferer behaves according to a parametric model but the values of the model parameters are unknown. We explore the necessary number of sensing steps to gather sufficient knowledge…

Information Theory · Computer Science 2024-10-11 Vincent Corlay , Jean-Christophe Sibel , Nicolas Gresset

Deep neural networks have become foundational to advancements in multiple domains, including recommendation systems, natural language processing, and so on. Despite their successes, these models often contain incompatible parameters that…

Machine Learning · Computer Science 2025-03-04 Zheqi Lv , Keming Ye , Zishu Wei , Qi Tian , Shengyu Zhang , Wenqiao Zhang , Wenjie Wang , Kun Kuang , Tat-Seng Chua , Fei Wu

Background: Acute kidney injury (AKI) is a common complication in hospitalized patients and a common cause for chronic kidney disease (CKD) and increased hospital cost and mortality. By timely detection of AKI and AKI progression, effective…

Precision medicine involves developing individualized treatment regimes (ITRs) which allow for treatment decisions to be tailored to patient characteristics. Naturally, the identification of the optimal regime, that is, the rule which…

Methodology · Statistics 2025-09-30 Misha Dolmatov , Erica E. M. Moodie , David A. Stephens , Dipankar Bandyopadhyay

The problem of minimizing queueing delay of opportunistic access of multiple continuous time Markov channels is considered. A new access policy based on myopic sensing and adaptive transmission (MS-AT) is proposed. Under the framework of…

Optimization and Control · Mathematics 2011-08-02 Shiyao Chen , Lang Tong , Qing Zhao

We introduce the notion of quantum Markov decision process (qMDP) as a semantic model of nondeterministic and concurrent quantum programs. It is shown by examples that qMDPs can be used in analysis of quantum algorithms and protocols. We…

Quantum Physics · Physics 2014-07-10 Shenggang Ying , Mingsheng Ying

Identifying the type of kidney stones can allow urologists to determine their formation cause, improving the early prescription of appropriate treatments to diminish future relapses. However, currently, the associated ex-vivo diagnosis…

Computer Vision and Pattern Recognition · Computer Science 2022-06-03 Daniel Flores-Araiza , Francisco Lopez-Tiro , Elias Villalvazo-Avila , Jonathan El-Beze , Jacques Hubert , Gilberto Ochoa-Ruiz , Christian Daul

Projected subgradient descent (PSD) has gained popularity for solving robust Markov decision processes (RMDPs) because it applies to a broader class of uncertainty sets than traditional dynamic programming. Existing work claims that RMDPs…

Optimization and Control · Mathematics 2026-04-24 Toshinori Kitamura , Arnob Ghosh , Alex Ayoub , Thang D. Chu , Csaba Szepesvári

We investigate whether temporal embedding models trained on longitudinal electronic health records can learn clinically meaningful representations without compromising predictive performance, and how architectural choices affect embedding…

Machine Learning · Computer Science 2026-04-17 Aditya Kumar , Mario A. Cypko , Oliver Amft
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