The genetics and pathogenesis of CAKUT
CM Kolvenbach, S Shril, F Hildebrandt - Nature Reviews Nephrology, 2023 - nature.com
Congenital anomalies of the kidney and urinary tract (CAKUT) comprise a large variety of
malformations that arise from defective kidney or urinary tract development and frequently …
malformations that arise from defective kidney or urinary tract development and frequently …
Federated learning in health care using structured medical data
W Oh, GN Nadkarni - Advances in kidney disease and health, 2023 - Elsevier
The success of machine learning–based studies is largely subjected to accessing a large
amount of data. However, accessing such data is typically not feasible within a single health …
amount of data. However, accessing such data is typically not feasible within a single health …
A comparative analysis of meta-heuristic optimization algorithms for feature selection on ML-based classification of heart-related diseases
This study aims to use a machine learning (ML)-based enhanced diagnosis and survival
model to predict heart disease and survival in heart failure by combining the cuckoo search …
model to predict heart disease and survival in heart failure by combining the cuckoo search …
Chronic kidney disease prediction using boosting techniques based on clinical parameters
Chronic kidney disease (CKD) has become a major global health crisis, causing millions of
yearly deaths. Predicting the possibility of a person being affected by the disease will allow …
yearly deaths. Predicting the possibility of a person being affected by the disease will allow …
Mortality prediction with adaptive feature importance recalibration for peritoneal dialysis patients
The study aims to develop AICare, an interpretable mortality prediction model, using
electronic medical records (EMR) from follow-up visits for end-stage renal disease (ESRD) …
electronic medical records (EMR) from follow-up visits for end-stage renal disease (ESRD) …
Machine learning approach to predict in‐hospital mortality in patients admitted for peripheral artery disease in the United States
Background Peripheral artery disease (PAD) affects> 10 million people in the United States.
PAD is associated with poor outcomes, including premature death. Machine learning (ML) …
PAD is associated with poor outcomes, including premature death. Machine learning (ML) …
Machine-Learning-Based Prediction Modelling in Primary Care: State-of-the-Art Review
Primary care has the potential to be transformed by artificial intelligence (AI) and, in
particular, machine learning (ML). This review summarizes the potential of ML and its …
particular, machine learning (ML). This review summarizes the potential of ML and its …
Short Timeframe Prediction of Kidney Failure among Patients with Advanced Chronic Kidney Disease
MM Klamrowski, R Klein, C McCudden… - Clinical …, 2023 - academic.oup.com
Background Development of a short timeframe (6–12 months) kidney failure risk prediction
model may serve to improve transitions from advanced chronic kidney disease (CKD) to …
model may serve to improve transitions from advanced chronic kidney disease (CKD) to …
Kidney failure detection and predictive analytics for ckd using machine learning procedures
SM Nimmagadda, SS Agasthi, A Shai… - … Methods in Engineering, 2023 - Springer
Kidneys are the functional units of our body. They assist in body balance by filtering the
wastes, toxins, and excess water from the bloodstream and are carried out of the body …
wastes, toxins, and excess water from the bloodstream and are carried out of the body …
Predicting CKD progression using time-series clustering and light gradient boosting machines
H Saito, H Yoshimura, K Tanaka, H Kimura… - Scientific Reports, 2024 - nature.com
Predicting the transition of kidney function in chronic kidney disease is difficult as specific
symptoms are lacking and often overlooked, and progress occurs due to complicating …
symptoms are lacking and often overlooked, and progress occurs due to complicating …