Neda Rostamzadeh
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View article: High-Throughput Computing to Detect Harmful Drug-Drug Interactions in Older Adults: Protocol for a Population-Based Cohort Study
High-Throughput Computing to Detect Harmful Drug-Drug Interactions in Older Adults: Protocol for a Population-Based Cohort Study Open
Background Drug-drug interactions (DDIs) are a major concern, especially for older adults taking multiple medications. Although Health Canada and the US Food and Drug Administration (FDA) use population-based studies to identify adverse dr…
View article: 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
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 Open
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 p…
View article: Visual Analytics for Predicting Disease Outcomes Using Laboratory Test Results
Visual Analytics for Predicting Disease Outcomes Using Laboratory Test Results Open
Laboratory tests play an essential role in the early and accurate diagnosis of diseases. In this paper, we propose SUNRISE, a visual analytics system that allows the user to interactively explore the relationships between laboratory test r…
View article: VERONICA: Visual Analytics for Identifying Feature Groups in Disease Classification
VERONICA: Visual Analytics for Identifying Feature Groups in Disease Classification Open
The use of data analysis techniques in electronic health records (EHRs) offers great promise in improving predictive risk modeling. Although useful, these analysis techniques often suffer from a lack of interpretability and transparency, e…
View article: Visual Analytics for Electronic Health Records: A Review
Visual Analytics for Electronic Health Records: A Review Open
The increasing use of electronic health record (EHR)-based systems has led to the generation of clinical data at an unprecedented rate, which produces an untapped resource for healthcare experts to improve the quality of care. Despite the …
View article: Predicting Acute Kidney Injury: A Machine Learning Approach Using Electronic Health Records
Predicting Acute Kidney Injury: A Machine Learning Approach Using Electronic Health Records Open
Acute kidney injury (AKI) is a common complication in hospitalized patients and can result in increased hospital stay, health-related costs, mortality and morbidity. A number of recent studies have shown that AKI is predictable and avoidab…
View article: Machine Learning for Identifying Medication-Associated Acute Kidney Injury
Machine Learning for Identifying Medication-Associated Acute Kidney Injury Open
One of the prominent problems in clinical medicine is medication-induced acute kidney injury (AKI). Avoiding this problem can prevent patient harm and reduce healthcare expenditures. Several researches have been conducted to identify AKI-a…
View article: Visual Analytics for Dimension Reduction and Cluster Analysis of High Dimensional Electronic Health Records
Visual Analytics for Dimension Reduction and Cluster Analysis of High Dimensional Electronic Health Records Open
Recent advancement in EHR-based (Electronic Health Record) systems has resulted in producing data at an unprecedented rate. The complex, growing, and high-dimensional data available in EHRs creates great opportunities for machine learning …
View article: Multiple Regression Analysis and Frequent Itemset Mining of Electronic Medical Records: A Visual Analytics Approach Using VISA_M3R3
Multiple Regression Analysis and Frequent Itemset Mining of Electronic Medical Records: A Visual Analytics Approach Using VISA_M3R3 Open
Medication-induced acute kidney injury (AKI) is a well-known problem in clinical medicine. This paper reports the first development of a visual analytics (VA) system that examines how different medications associate with AKI. In this paper…
View article: Data-Driven Activities Involving Electronic Health Records: An Activity and Task Analysis Framework for Interactive Visualization Tools
Data-Driven Activities Involving Electronic Health Records: An Activity and Task Analysis Framework for Interactive Visualization Tools Open
Electronic health records (EHRs) can be used to make critical decisions, to study the effects of treatments, and to detect hidden patterns in patient histories. In this paper, we present a framework to identify and analyze EHR-data-driven …