AIMC Topic: Ontario

Clear Filters Showing 1 to 10 of 45 articles

Detecting and Remediating Harmful Data Shifts for the Responsible Deployment of Clinical AI Models.

JAMA network open
IMPORTANCE: Clinical artificial intelligence (AI) systems are susceptible to performance degradation due to data shifts, which can lead to erroneous predictions and potential patient harm. Proactively detecting and mitigating these shifts is crucial ...

Transformer-based deep learning ensemble framework predicts autism spectrum disorder using health administrative and birth registry data.

Scientific reports
Early diagnosis and access to resources, support and therapy are critical for improving long-term outcomes for children with autism spectrum disorder (ASD). ASD is typically detected using a case-finding approach based on symptoms and family history,...

Predicting Clinical Outcomes at the Toronto General Hospital Transitional Pain Service via the Manage My Pain App: Machine Learning Approach.

JMIR medical informatics
BACKGROUND: Chronic pain is a complex condition that affects more than a quarter of people worldwide. The development and progression of chronic pain are unique to each individual due to the contribution of interacting biological, psychological, and ...

Machine learning prediction of premature death from multimorbidity among people with inflammatory bowel disease: a population-based retrospective cohort study.

CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne
BACKGROUND: Multimorbidity, the co-occurrence of 2 or more chronic conditions, is important in patients with inflammatory bowel disease (IBD) given its association with complex care plans, poor health outcomes, and excess mortality. Our objectives we...

Of Lyme disease and machine learning in a One Health world.

American journal of veterinary research
OBJECTIVE: Lyme disease is a vector-borne emerging zoonosis in Ontario driven by human population growth and climate change. Lyme disease is also a prime example of the One Health concept. While little can be done to immediately reverse climate chang...

A Cross-Sectional Survey of Optometrists in Canada Regarding Referral Patterns and a Needs Assessment for an Artificial Intelligence Referral Screening Tool for Epiretinal Membrane.

Ophthalmic surgery, lasers & imaging retina
BACKGROUND AND OBJECTIVE: This study evaluated optometrists' referral patterns for epiretinal membrane (ERM) patients in Ontario, Canada, and their attitudes towards an artificial intelligence (AI) tool for improving referral accuracy. An anonymous o...

Predicting few disinfection byproducts in the water distribution systems using machine learning models.

Environmental science and pollution research international
Concerns regarding disinfection byproducts (DBPs) in drinking water persist, with measurements in water treatment plants (WTPs) being relatively easier than those in water distribution systems (WDSs) due to accessibility challenges, especially during...

Machine learning models provide modest accuracy in predicting clinical impact of porcine reproductive and respiratory syndrome type 2 in Canadian sow herds.

American journal of veterinary research
OBJECTIVE: To determine the predictive potential of the open reading frame 5 nucleotide sequence of porcine reproductive and respiratory syndrome (PRRS) virus and the basic demographic data on the severity of the impact on selected production paramet...

Data-Driven Decision Support Tool Co-Development with a Primary Health Care Practice Based Learning Network.

F1000Research
BACKGROUND: The Alliance for Healthier Communities is a learning health system that supports Community Health Centres (CHCs) across Ontario, Canada to provide team-based primary health care to people who otherwise experience barriers to care. This ca...

Regulating professional ethics in a context of technological change.

BMC medical ethics
BACKGROUND: Technological change is impacting the work of health professionals, especially with recent developments in artificial intelligence. Research has raised many ethical considerations respecting clinical applications of artificial intelligenc...