High-Throughput Computing to Automate Population-Based Studies to Detect the 30-Day Risk of Adverse Outcomes After New Outpatient Medication Use in Older Adults with Chronic Kidney Disease: A Clinical Research Protocol
Background: Safety issues are detected in about one third of prescription drugs in the years following regulatory agency approval. Older adults, especially those with chronic kidney disease, are at particular risk of adverse reactions to prescription drugs. This protocol describes a new approach tha...
Main Authors: | Sheikh S. Abdullah, Neda Rostamzadeh, Flory T. Muanda, Eric McArthur, Matthew A. Weir, Jessica M. Sontrop, Richard B. Kim, Sedig Kamran, Amit X. Garg |
---|---|
Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2024-01-01
|
Series: | Canadian Journal of Kidney Health and Disease |
Online Access: | https://doi.org/10.1177/20543581231221891 |
Similar Items
-
Predicting Acute Kidney Injury: A Machine Learning Approach Using Electronic Health Records
by: Sheikh S. Abdullah, et al.
Published: (2020-08-01) -
Visual Analytics for Dimension Reduction and Cluster Analysis of High Dimensional Electronic Health Records
by: Sheikh S. Abdullah, et al.
Published: (2020-05-01) -
Visual Analytics for Predicting Disease Outcomes Using Laboratory Test Results
by: Neda Rostamzadeh, et al.
Published: (2022-02-01) -
VERONICA: Visual Analytics for Identifying Feature Groups in Disease Classification
by: Neda Rostamzadeh, et al.
Published: (2021-08-01) -
Multiple Regression Analysis and Frequent Itemset Mining of Electronic Medical Records: A Visual Analytics Approach Using VISA_M3R3
by: Sheikh S. Abdullah, et al.
Published: (2020-03-01)