A comparative analysis of machine learning models: a case study in predicting chronic kidney disease

H Iftikhar, M Khan, Z Khan, F Khan, HM Alshanbari… - Sustainability, 2023 - mdpi.com
In the modern world, chronic kidney disease is one of the most severe diseases that
negatively affects human life. It is becoming a growing problem in both developed and …

Clinical risk assessment of patients with chronic kidney disease by using clinical data and multivariate models

Z Chen, X Zhang, Z Zhang - International urology and nephrology, 2016 - Springer
Purpose Timely risk assessment of chronic kidney disease (CKD) and proper community-
based CKD monitoring are important to prevent patients with potential risk from further …

A semi-supervised multi-task learning approach for predicting short-term kidney disease evolution

M Bernardini, L Romeo, E Frontoni… - IEEE journal of …, 2021 - ieeexplore.ieee.org
Kidney Disease (KD) may hide complex causes and is associated with a tremendous socio-
economic impact. Timely identification and management from the first level of medical care …

Development of risk prediction equations for incident chronic kidney disease

RG Nelson, ME Grams, SH Ballew, Y Sang, F Azizi… - Jama, 2019 - jamanetwork.com
Importance Early identification of individuals at elevated risk of developing chronic kidney
disease (CKD) could improve clinical care through enhanced surveillance and better …

Predicting outcomes of chronic kidney disease from EMR data based on Random Forest Regression

J Zhao, S Gu, A McDermaid - Mathematical biosciences, 2019 - Elsevier
Chronic kidney disease (CKD) is prevalent across the world, and kidney function is well
defined by an estimated glomerular filtration rate (eGFR). The progression of kidney disease …

Computer-aided diagnosis of chronic kidney disease in developing countries: A comparative analysis of machine learning techniques

A Sobrinho, ACMDS Queiroz, LD Da Silva… - IEEE …, 2020 - ieeexplore.ieee.org
The high incidence and prevalence of chronic kidney disease (CKD), often caused by late
diagnoses, is a critical public health problem, especially in developing countries such as …

Clinical prediction models for progression of chronic kidney disease to end-stage kidney failure under pre-dialysis nephrology care: results from the Chronic Kidney …

T Hasegawa, K Sakamaki, F Koiwa, T Akizawa… - Clinical and …, 2019 - Springer
Background Reliable prediction tools are needed to identify patients with chronic kidney
disease (CKD) at greater risk of developing end-stage kidney failure (ESKF). We developed …

Enhancing the early detection of chronic kidney disease: a robust machine learning model

MS Arif, A Mukheimer, D Asif - Big Data and Cognitive Computing, 2023 - mdpi.com
Clinical decision-making in chronic disorder prognosis is often hampered by high variance,
leading to uncertainty and negative outcomes, especially in cases such as chronic kidney …

Machine‐learning–based early prediction of end‐stage renal disease in patients with diabetic kidney disease using clinical trials data

S Belur Nagaraj, MJ Pena, W Ju… - Diabetes, Obesity …, 2020 - Wiley Online Library
Aim To predict end‐stage renal disease (ESRD) in patients with type 2 diabetes by using
machine‐learning models with multiple baseline demographic and clinical characteristics …

Increasing tendency of urine protein is a risk factor for rapid eGFR decline in patients with CKD: A machine learning-based prediction model by using a big database

D Inaguma, A Kitagawa, R Yanagiya, A Koseki… - PLoS …, 2020 - journals.plos.org
Artificial intelligence is increasingly being adopted in medical fields to predict various
outcomes. In particular, chronic kidney disease (CKD) is problematic because it often …