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Background: Cirrhosis is a progressive liver disease with high mortality and frequent complications, notably acute kidney injury (AKI), which occurs in up to 50% of hospitalized patients and worsens outcomes. AKI stems from complex…

机器学习 · 计算机科学 2025-08-15 Li Sun , Shuheng Chen , Junyi Fan , Yong Si , Minoo Ahmadi , Elham Pishgar , Kamiar Alaei , Maryam Pishgar

Deep learning (DL) can aid doctors in detecting worsening patient states early, affording them time to react and prevent bad outcomes. While DL-based early warning models usually work well in the hospitals they were trained for, they tend…

Acute Kidney Injury (AKI) is a common clinical syndrome characterized by the rapid loss of kidney excretory function, which aggravates the clinical severity of other diseases in a large number of hospitalized patients. Accurate early…

Background: Acute kidney injury (AKI) is a clinical syndrome affecting almost one fifth of hospitalized patients, as well as more than half of the patients who are admitted to the intensive care unit (ICU). Stratifying AKI patients into…

Sepsis is a severe condition that causes the body to respond incorrectly to an infection. This reaction can subsequently cause organ failure, a major one being acute kidney injury (AKI). For septic patients, approximately 50% develop AKI,…

机器学习 · 计算机科学 2024-12-06 Aleyeh Roknaldin , Zehao Zhang , Jiayuan Xu , Kamiar Alaei , Maryam Pishgar

An accurate model of patient-specific kidney graft survival distributions can help to improve shared-decision making in the treatment and care of patients. In this paper, we propose a deep learning method that directly models the survival…

机器学习 · 计算机科学 2017-05-30 Margaux Luck , Tristan Sylvain , Héloïse Cardinal , Andrea Lodi , Yoshua Bengio

Deep learning developments have improved medical imaging diagnoses dramatically, increasing accuracy in several domains. Nonetheless, obstacles continue to exist because of the requirement for huge datasets and legal limitations on data…

计算机视觉与模式识别 · 计算机科学 2024-10-01 Ivan Reyes-Amezcua , Michael Rojas-Ruiz , Gilberto Ochoa-Ruiz , Andres Mendez-Vazquez , Christian Daul

In clinical data sets we often find static information (e.g. patient gender, blood type, etc.) combined with sequences of data that are recorded during multiple hospital visits (e.g. medications prescribed, tests performed, etc.). Recurrent…

机器学习 · 计算机科学 2016-11-18 Cristóbal Esteban , Oliver Staeck , Yinchong Yang , Volker Tresp

Chronic kidney disease (CKD) is a major global health issue, affecting over 10% of the population and causing significant mortality. While kidney biopsy remains the gold standard for CKD diagnosis and treatment, the lack of comprehensive…

Chronic Kidney Disease (CKD), where delayed recognition implies premature mortality, is currently experiencing a globally increasing incidence and high cost to health systems. Data mining allows discovering subtle patterns in CKD indicators…

机器学习 · 计算机科学 2023-06-21 Pedro A. Moreno-Sanchez

Kidney abnormality detection is required for all preclinical drug development. It involves a time-consuming and costly examination of hundreds to thousands of whole-slide images per drug safety study, most of which are normal, to detect any…

计算机视觉与模式识别 · 计算机科学 2025-09-03 Ivan Slootweg , Natalia P. García-De-La-Puente , Geert Litjens , Salma Dammak

Progression to dialysis or end-stage renal disease is a rare but clinically important outcome. Clinicians need evidence on how medication exposures influence downstream risk. We constructed a fixed-window EHR cohort (90-day observation,…

机器学习 · 计算机科学 2026-04-28 Kalyani P. Pande , Evan Yang , Bryan Zhu , Sandeep K. Mallipattu , Alisa Yurovsky , Tengfei Ma

Chronic kidney disease (CKD) is a global health challenge characterized by progressive kidney function decline, often culminating in end-stage kidney disease (ESKD) and increased mortality. To address the limitations such as the extended…

统计方法学 · 统计学 2025-04-11 Tuo Wang , Yu Du

We study the behavior of a Time-Aware Long Short-Term Memory Autoencoder, a state-of-the-art method, in the context of learning latent representations from irregularly sampled patient data. We identify a key issue in the way such recurrent…

机器学习 · 计算机科学 2019-02-12 Duc Thanh Anh Luong , Varun Chandola

A kidney transplant can improve the life expectancy and quality of life of patients with end-stage renal failure. Even more patients could be helped with a transplant if the rate of kidneys that are discarded and not transplanted could be…

The in-vivo identification of the kidney stone types during an ureteroscopy would be a major medical advance in urology, as it could reduce the time of the tedious renal calculi extraction process, while diminishing infection risks.…

Chronic Kidney Disease (CKD) is an increasingly prevalent condition affecting 13% of the US population. The disease is often a silent condition, making its diagnosis challenging. Identifying CKD stages from standard office visit records can…

定量方法 · 定量生物学 2017-12-07 M. Bhattacharya , C. Jurkovitz , H. Shatkay

Objective: Our objective is to develop and validate TrajVis, an interactive tool that assists clinicians in using artificial intelligence (AI) models to leverage patients' longitudinal electronic medical records (EMR) for personalized…

人机交互 · 计算机科学 2024-01-17 Zuotian Li , Xiang Liu , Ziyang Tang , Pengyue Zhang , Nanxin Jin , Michael Eadon , Qianqian Song , Yingjie Chen , Jing Su

Determining the type of kidney stones is crucial for prescribing appropriate treatments to prevent recurrence. Currently, various approaches exist to identify the type of kidney stones. However, obtaining results through the reference ex…

计算机视觉与模式识别 · 计算机科学 2025-05-26 Carlos Salazar-Ruiz , Francisco Lopez-Tiro , Ivan Reyes-Amezcua , Clement Larose , Gilberto Ochoa-Ruiz , Christian Daul

Prediction of the future trajectory of a disease is an important challenge for personalized medicine and population health management. However, many complex chronic diseases exhibit large degrees of heterogeneity, and furthermore there is…

机器学习 · 统计学 2016-08-17 Joseph Futoma , Mark Sendak , C. Blake Cameron , Katherine Heller