AIMC Topic: Ontario

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Comparing an Artificial Neural Network to Logistic Regression for Predicting ED Visit Risk Among Patients With Cancer: A Population-Based Cohort Study.

Journal of pain and symptom management
CONTEXT: Prior work using symptom burden to predict emergency department (ED) visits among patients with cancer has used traditional statistical methods such as logistic regression (LR). Machine learning approaches for prediction, such as artificial ...

Sensor-based machine learning for workflow detection and as key to detect expert level in laparoscopic suturing and knot-tying.

Surgical endoscopy
INTRODUCTION: The most common way of assessing surgical performance is by expert raters to view a surgical task and rate a trainee's performance. However, there is huge potential for automated skill assessment and workflow analysis using modern techn...

Associations between management practices and within-pen prevalence of calf diarrhea and respiratory disease on dairy farms using automated milk feeders.

Journal of dairy science
Data on management practices used with automated milk feeders (AMF) are needed to identify factors associated with calf health in these systems. The objectives of this observational, longitudinal, cross-sectional study were to estimate the prevalence...

Mapping real-time air pollution health risk for environmental management: Combining mobile and stationary air pollution monitoring with neural network models.

Journal of environmental management
Air pollution poses health concerns at the global scale. The challenge of managing air pollution is significant because of the many air pollutants, insufficient funds for monitoring and abatement programs, and political and social challenges in defin...

A Guide for Implementing an A.I-Driven Initiative in Rural Northern Ontario.

Studies in health technology and informatics
Diagnosing pulmonary embolism (PE) often requires specialized expertise in interpreting x-rays and radiographic images, resources that are mostly limited in rural settings. This paper explores the development of an electronic health record (EHR) syst...

Empowering Health: Model for Sustainable AI Implementation.

Studies in health technology and informatics
OntarioMD (OMD), a leader in digital health, focuses on harnessing artificial intelligence (AI) technologies to reduce administrative burden and enhance patient care in primary care. Building on 20 years of digital health experience, OMD has establis...

Lack of Data Access, but Not Availability, Hinders AI Training for High-Risk Conditions in Ontario.

Studies in health technology and informatics
Advanced disease prediction is an important step toward achieving a proactive healthcare system. New technologies such as artificial intelligence are very promising in their ability to predict the onset of future disease much earlier than has been po...

Artificial intelligence in primary care practice: Qualitative study to understand perspectives on using AI to derive patient social data.

Canadian family physician Medecin de famille canadien
OBJECTIVE: To understand the perspectives of primary care clinicians and health system leaders on the use of artificial intelligence (AI) to derive information about patients' social determinants of health.