AIMC Topic: Alberta
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Automated ASPECTS on Noncontrast CT Scans in Patients with Acute Ischemic Stroke Using Machine Learning.
AJNR. American journal of neuroradiology
Nov 29, 2018
BACKGROUND AND PURPOSE: Alberta Stroke Program Early CT Score (ASPECTS) was devised as a systematic method to assess the extent of early ischemic change on noncontrast CT (NCCT) in patients with acute ischemic stroke (AIS). Our aim was to automate AS...
Detection of early infarction signs with machine learning-based diagnosis by means of the Alberta Stroke Program Early CT score (ASPECTS) in the clinical routine.
Neuroradiology
Jul 31, 2018
PURPOSE: New software solutions emerged to support radiologists in image interpretation in acute ischemic stroke. This study aimed to validate the performance of computer-aided assessment of the Alberta Stroke Program Early CT score (ASPECTS) for det...
Humans
Observer Variation
Machine Learning
Alberta
Software
Aged, 80 and over
Adult
Stroke
Sensitivity and Specificity
Infarction, Middle Cerebral Artery
Male
Brain Ischemia
Tomography, X-Ray Computed
Middle Aged
Female
Predictive Value of Tests
Aged
Radiographic Image Interpretation, Computer-Assisted
Primary care physicians' perceived barriers, facilitators and strategies to enhance conservative care for older adults with chronic kidney disease: a qualitative descriptive study.
Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
Dec 17, 2015
BACKGROUND: Although primary care physicians (PCPs) are often responsible for the routine care of older adults with chronic kidney disease (CKD), there is a paucity of evidence regarding their perspectives and practice of conservative (non-dialysis) ...
Integrating large language models with human expertise for disease detection in electronic health records.
Computers in biology and medicine
Jun 1, 2025
OBJECTIVE: Electronic health records (EHR) are widely available to complement administrative data-based disease surveillance and healthcare performance evaluation. Defining conditions from EHR is labour-intensive and requires extensive manual labelli...
Assessing the validity of ICD-10 administrative data in coding comorbidities.
BMJ health & care informatics
May 13, 2025
OBJECTIVES: Administrative data are commonly used to inform chronic disease prevalence and support health informatic research. This study assessed the validity of coding comorbidities in the International Classification of Diseases, 10th Revision (IC...
Utilizing large language models for detecting hospital-acquired conditions: an empirical study on pulmonary embolism.
Journal of the American Medical Informatics Association : JAMIA
May 1, 2025
OBJECTIVES: Adverse event detection from Electronic Medical Records (EMRs) is challenging due to the low incidence of the event, variability in clinical documentation, and the complexity of data formats. Pulmonary embolism as an adverse event (PEAE) ...
A deep learning and radiomics based Alberta stroke program early CT score method on CTA to evaluate acute ischemic stroke.
Journal of X-ray science and technology
Jan 1, 2024
BACKGROUND: Alberta stroke program early CT score (ASPECTS) is a semi-quantitative evaluation method used to evaluate early ischemic changes in patients with acute ischemic stroke, which can guide physicians in treatment decisions and prognostic judg...
Understanding challenges of using routinely collected health data to address clinical care gaps: a case study in Alberta, Canada.
BMJ open quality
Jan 1, 2022
High-quality data are fundamental to healthcare research, future applications of artificial intelligence and advancing healthcare delivery and outcomes through a learning health system. Although routinely collected administrative health and electroni...
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