English
Related papers

Related papers: Estimand framework development for eGFR slope esti…

200 papers

Objective: To improve prediction of Chronic Kidney Disease (CKD) progression to End Stage Renal Disease (ESRD) using machine learning (ML) and deep learning (DL) models applied to an integrated clinical and claims dataset of varying…

Quantitative Methods · Quantitative Biology 2025-05-06 Yubo Li , Rema Padman

Accurate and interpretable prediction of estimated glomerular filtration rate (eGFR) is essential for managing chronic kidney disease (CKD) and supporting clinical decisions. Recent advances in Large Multimodal Models (LMMs) have shown…

Machine Learning · Computer Science 2025-07-31 Peng-Yi Wu , Pei-Cing Huang , Ting-Yu Chen , Chantung Ku , Ming-Yen Lin , Yihuang Kang

Chronic kidney disease (CKD) is a significant public health challenge, often progressing to end-stage renal disease (ESRD) if not detected and managed early. Early intervention, warranted by silent disease progression, can significantly…

Machine Learning · Computer Science 2024-11-19 Zachary Dana , Ahmed Ammar Naseer , Botros Toro , Sumanth Swaminathan

Identifying prognostic factors for disease progression is a cornerstone of medical research. Repeated assessments of a marker outcome are often used to evaluate disease progression, and the primary research question is to identify factors…

Computation · Statistics 2022-10-24 Brian Kwan , Lin Liu , David Strong , H. Irene Su , Loki Natarajan

The estimated Glomerular Filtration Rate (eGFR) is an essential indicator of kidney function in clinical practice. Although traditional equations and Machine Learning (ML) models using clinical and laboratory data can estimate eGFR,…

Machine Learning · Computer Science 2024-09-05 Chih-Yuan Li , Jun-Ting Wu , Chan Hsu , Ming-Yen Lin , Yihuang Kang

In clinical trials where long follow-up is required to measure the primary outcome of interest, there is substantial interest in using an accepted surrogate outcome that can be measured earlier in time or with less cost to estimate a…

Methodology · Statistics 2024-12-19 Xuan Wang , Jie Zhou , Layla Parast , Tom Greene

Introduction: Kidney function is reported using estimates of glomerular filtration rate (eGFR). However, eGFR values are recorded without reference to the creatinine (SCr) assays used to derive them, and newer assays were introduced at…

Quantitative Methods · Quantitative Biology 2014-09-05 Norman Poh , Andrew McGovern , Simon de Lusignan

Randomized controlled trials (RCTs) are the standard for evaluating the effectiveness of clinical interventions. To address the limitations of RCTs on real-world populations, we developed a methodology that uses a large observational…

Machine Learning · Computer Science 2024-10-21 Panayiotis Petousis , David Gordon , Susanne B. Nicholas , Alex A. T. Bui

Chronic kidney disease (CKD) affects millions worldwide and progresses irreversibly through stages culminating in end-stage renal disease (ESRD) and death. Outcome trials in CKD traditionally employ time-to-first-event analyses using the…

Methodology · Statistics 2026-01-27 Jiren Sun , Tuo Wang , Yu Du

As the global population ages, the incidence of Chronic Kidney Disease (CKD) is rising. CKD often remains asymptomatic until advanced stages, which significantly burdens both the healthcare system and patient quality of life. This research…

Artificial Intelligence · Computer Science 2024-04-18 Nantika Nguycharoen

This study explores the potential of utilizing administrative claims data, combined with advanced machine learning and deep learning techniques, to predict the progression of Chronic Kidney Disease (CKD) to End-Stage Renal Disease (ESRD).…

Machine Learning · Computer Science 2024-10-28 Yubo Li , Saba Al-Sayouri , Rema Padman

Early detection of chronic kidney disease (CKD) is essential for preventing progression to end-stage renal disease. However, existing screening tools - primarily developed using populations from high-income countries - often underperform in…

Chronic kidney disease (CKD) is a gradual loss of renal function over time, and it increases the risk of mortality, decreased quality of life, as well as serious complications. The prevalence of CKD has been increasing in the last couple of…

Machine Learning · Computer Science 2020-11-18 Jinghe Zhang , Kamran Kowsari , Mehdi Boukhechba , James Harrison , Jennifer Lobo , Laura Barnes

Chronic Kidney Disease (CKD) is one of the widespread Chronic diseases with no known ultimo cure and high morbidity. Research demonstrates that progressive Chronic Kidney Disease (CKD) is a heterogeneous disorder that significantly impacts…

Machine Learning · Computer Science 2025-01-28 K M Tawsik Jawad , Anusha Verma , Fathi Amsaad , Lamia Ashraf

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…

Machine Learning · Computer Science 2023-06-21 Pedro A. Moreno-Sanchez

Chronic Kidney Disease (CKD) constitutes a major global medical burden, marked by the gradual deterioration of renal function, which results in the impaired clearance of metabolic waste and disturbances in systemic fluid homeostasis. Owing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Anas Bin Ayub , Nilima Sultana Niha , Md. Zahurul Haque

Chronic kidney disease (CKD) has a poor prognosis due to excessive risk factors and comorbidities associated with it. The early detection of CKD faces challenges of insufficient medical histories of positive patients and complicated risk…

Machine Learning · Computer Science 2020-12-08 Yu Wang , Ziqiao Guan , Wei Hou , Fusheng Wang

Chronic Kidney Disease (CKD) affects nearly 10\% of the global population and often progresses to end-stage renal failure. Accurate prognosis prediction is vital for timely interventions and resource optimization. We present a…

Artificial Intelligence · Computer Science 2025-11-19 Yohan Lee , DongGyun Kang , SeHoon Park , Sa-Yoon Park , Kwangsoo Kim

In order for clinicians to manage disease progression and make effective decisions about drug dosage, treatment regimens or scheduling follow up appointments, it is necessary to be able to identify both short and long-term trends in…

Quantitative Methods · Quantitative Biology 2016-12-06 Norman Poh , Simon Bull , Santosh Tirunagari , Nicholas Cole , Simon de Lusignan

A patient's estimated glomerular filtration rate (eGFR) can provide important information about disease progression and kidney function. Traditionally, an eGFR time series is interpreted by a human expert labelling it as stable or unstable.…

Machine Learning · Computer Science 2016-05-18 Santosh Tirunagari , Simon Bull , Norman Poh
‹ Prev 1 2 3 10 Next ›