Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review
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 …
Advancements and prospects of machine learning in medical diagnostics: unveiling the future of diagnostic precision
Abstract Machine learning (ML) has emerged as a versatile and powerful tool in various
fields of medicine, revolutionizing early disease diagnosis, particularly in cases where …
fields of medicine, revolutionizing early disease diagnosis, particularly in cases where …
A deep neural network for early detection and prediction of chronic kidney disease
Diabetes and high blood pressure are the primary causes of Chronic Kidney Disease (CKD).
Glomerular Filtration Rate (GFR) and kidney damage markers are used by researchers …
Glomerular Filtration Rate (GFR) and kidney damage markers are used by researchers …
Intelligent diagnostic prediction and classification models for detection of kidney disease
Kidney disease is a major public health concern that has only recently emerged. Toxins are
removed from the body by the kidneys through urine. In the early stages of the condition, the …
removed from the body by the kidneys through urine. In the early stages of the condition, the …
Artificial intelligence-enabled decision support in nephrology
Kidney pathophysiology is often complex, nonlinear and heterogeneous, which limits the
utility of hypothetical-deductive reasoning and linear, statistical approaches to diagnosis and …
utility of hypothetical-deductive reasoning and linear, statistical approaches to diagnosis and …
Development and internal validation of supervised machine learning algorithms for predicting the risk of surgical site infection following minimally invasive …
H Wang, T Fan, B Yang, Q Lin, W Li, M Yang - Frontiers in Medicine, 2021 - frontiersin.org
Purpose: Machine Learning (ML) is rapidly growing in capability and is increasingly applied
to model outcomes and complications in medicine. Surgical site infections (SSI) are a …
to model outcomes and complications in medicine. Surgical site infections (SSI) are a …
Large-scale study of temporal shift in health insurance claims
Most machine learning models for predicting clinical outcomes are developed using
historical data. Yet, even if these models are deployed in the near future, dataset shift over …
historical data. Yet, even if these models are deployed in the near future, dataset shift over …
Investigation on explainable machine learning models to predict chronic kidney diseases
Chronic kidney disease (CKD) is a major worldwide health problem, affecting a large
proportion of the world's population and leading to higher morbidity and death rates. The …
proportion of the world's population and leading to higher morbidity and death rates. The …
Performance analysis of conventional machine learning algorithms for identification of chronic kidney disease in type 1 diabetes mellitus patients
Chronic kidney disease (CKD) is one of the severe side effects of type 1 diabetes mellitus
(T1DM). However, the detection and diagnosis of CKD are often delayed because of its …
(T1DM). However, the detection and diagnosis of CKD are often delayed because of its …
A new era in the science and care of kidney diseases
Notable progress in basic, translational and clinical nephrology research has been made
over the past five decades. Nonetheless, many challenges remain, including obstacles to …
over the past five decades. Nonetheless, many challenges remain, including obstacles to …