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 …
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] Role of artificial intelligence in kidney disease
Q Yuan, H Zhang, T Deng, S Tang, X Yuan… - … Journal of Medical …, 2020 - ncbi.nlm.nih.gov
Artificial intelligence (AI), as an advanced science technology, has been widely used in
medical fields to promote medical development, mainly applied to early detections, disease …
medical fields to promote medical development, mainly applied to early detections, disease …
Artificial intelligence-based ensemble learning model for prediction of hepatitis C disease
Machine learning algorithms are excellent techniques to develop prediction models to
enhance response and efficiency in the health sector. It is the greatest approach to avoid the …
enhance response and efficiency in the health sector. It is the greatest approach to avoid the …
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) …
Quantifying impairment and disease severity using AI models trained on healthy subjects
Automatic assessment of impairment and disease severity is a key challenge in data-driven
medicine. We propose a framework to address this challenge, which leverages AI models …
medicine. We propose a framework to address this challenge, which leverages AI models …
[HTML][HTML] Application of artificial intelligence in renal disease
L Yao, H Zhang, M Zhang, X Chen, J Zhang, J Huang… - Clinical eHealth, 2021 - Elsevier
Artificial intelligence (AI) has been applied widely in almost every area of our daily lives, due
to the growth of computing power, advances in methods and techniques, and the explosion …
to the growth of computing power, advances in methods and techniques, and the explosion …
Artificial intelligence enabled applications in kidney disease
S Chaudhuri, A Long, H Zhang… - Seminars in …, 2021 - Wiley Online Library
Artificial intelligence (AI) is considered as the next natural progression of traditional
statistical techniques. Advances in analytical methods and infrastructure enable AI to be …
statistical techniques. Advances in analytical methods and infrastructure enable AI to be …
Big data in nephrology
A huge array of data in nephrology is collected through patient registries, large
epidemiological studies, electronic health records, administrative claims, clinical trial …
epidemiological studies, electronic health records, administrative claims, clinical trial …
[HTML][HTML] Prediction modeling—part 1: regression modeling
Risk prediction models are statistical models that estimate the probability of individuals
having a certain disease or clinical outcome based on a range of characteristics, and they …
having a certain disease or clinical outcome based on a range of characteristics, and they …