[HTML][HTML] Machine learning to predict end stage kidney disease in chronic kidney disease
Q Bai, C Su, W Tang, Y Li - Scientific reports, 2022 - nature.com
The purpose of this study was to assess the feasibility of machine learning (ML) in predicting
the risk of end-stage kidney disease (ESKD) from patients with chronic kidney disease …
the risk of end-stage kidney disease (ESKD) from patients with chronic kidney disease …
[HTML][HTML] Chronic kidney disease diagnosis using decision tree algorithms
Abstract Background Chronic Kidney Disease (CKD), ie, gradual decrease in the renal
function spanning over a duration of several months to years without any major symptoms, is …
function spanning over a duration of several months to years without any major symptoms, is …
Prediction of chronic kidney disease and its progression by artificial intelligence algorithms
Background and objective Aim of nephrologists is to delay the outcome and reduce the
number of patients undergoing renal failure (RF) by applying prevention protocols and …
number of patients undergoing renal failure (RF) by applying prevention protocols and …
[HTML][HTML] Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review
F Sanmarchi, C Fanconi, D Golinelli, D Gori… - Journal of …, 2023 - Springer
Objectives In this systematic review we aimed at assessing how artificial intelligence (AI),
including machine learning (ML) techniques have been deployed to predict, diagnose, and …
including machine learning (ML) techniques have been deployed to predict, diagnose, and …
A comprehensive analysis on detecting chronic kidney disease by employing machine learning algorithms
MM Nishat, F Faisal, RR Dip… - … on Pervasive Health …, 2021 - publications.eai.eu
Abstract INTRODUCTION: Chronic Kidney Disease refers to the slow, progressive
deterioration of kidney functions. However, the impairment is irreversible and imperceptible …
deterioration of kidney functions. However, the impairment is irreversible and imperceptible …
[HTML][HTML] Comparison and development of machine learning tools in the prediction of chronic kidney disease progression
J Xiao, R Ding, X Xu, H Guan, X Feng, T Sun… - Journal of translational …, 2019 - Springer
Background Urinary protein quantification is critical for assessing the severity of chronic
kidney disease (CKD). However, the current procedure for determining the severity of CKD …
kidney disease (CKD). However, the current procedure for determining the severity of CKD …
[HTML][HTML] A comparative assessment of artificial intelligence models used for early prediction and evaluation of chronic kidney disease
Abstract Chronic Kidney Disease (CKD) is one of the most prevalent and fatal diseases
influencing people on a larger that remains dormant until irreversible damage has been …
influencing people on a larger that remains dormant until irreversible damage has been …
Comprehensive performance assessment of deep learning models in early prediction and risk identification of chronic kidney disease
The incidence of chronic kidney disease (CKD) is rising rapidly around the globe.
Asymptomatic CKD is common and guideline-directed monitoring to predict CKD by various …
Asymptomatic CKD is common and guideline-directed monitoring to predict CKD by various …
[HTML][HTML] Chronic kidney disease prediction based on machine learning algorithms
Chronic kidney disease (CKD) is a dangerous ailment that can last a person's entire life and
is caused by either kidney malignancy or decreased kidney functioning. It is feasible to halt …
is caused by either kidney malignancy or decreased kidney functioning. It is feasible to halt …
Clinically applicable machine learning approaches to identify attributes of chronic kidney disease (CKD) for use in low-cost diagnostic screening
Objective: Chronic kidney disease (CKD) is a major public health concern worldwide. High
costs of late-stage diagnosis and insufficient testing facilities can contribute to high morbidity …
costs of late-stage diagnosis and insufficient testing facilities can contribute to high morbidity …