Predicting the onset of chronic kidney disease (CKD) for diabetic patients with aggregated longitudinal EMR data.
Chronic kidney disease (CKD) affects over 13% of the population, totaling more than 800 million individuals worldwide. Timely identification and intervention are crucial to delay CKD progression and improve patient outcomes. This research focuses on developing a predictive model to classify diabetic...
Saved in:
Main Authors: | Neda Aminnejad, Michelle Greiver, Huaxiong Huang |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2025-01-01
|
Series: | PLOS Digital Health |
Online Access: | https://doi.org/10.1371/journal.pdig.0000700 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Epidemiology of Chronic Kidney Diseases (CKD) in Malaysia and Pakistan, Pathophysiology of CKD-Associated Pruritus and Other CKD-Associated Dermatological Disorders
by: Inayat Ur Rehman, et al.
Published: (2020-04-01) -
A Study of Hypothyroidism in Chronic Kidney Disease (CKD) Patients
by: Sudharsanan V, et al.
Published: (2025-02-01) -
YUNUS EMRE BİBLİYOGRAFYASI
by: Mustafa CAN
Published: (2016-01-01) -
Serum hydroxycotinine was associated with chronic kidney disease (CKD): a cross-sectional study based on NHANES
by: Meng’en Zhu, et al.
Published: (2024-12-01) -
Prognostic Significance of Chronic Kidney Disease (CKD-EPI Equation) and Anemia in Patients with Chronic Heart Failure Secondary to Chagas Cardiomyopathy
by: Marcelo Arruda Nakazone, et al.
Published: (2020-01-01)