AIMC Topic: Canada

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Artificial intelligence for family medicine research in Canada: current state and future directions: Report of the CFPC AI Working Group.

Canadian family physician Medecin de famille canadien
OBJECTIVE: To understand the current landscape of artificial intelligence (AI) for family medicine (FM) research in Canada, identify how the College of Family Physicians of Canada (CFPC) could support near-term positive progress in this field, and st...

Accelerating AI Innovation in Healthcare Through Mentorship.

Studies in health technology and informatics
The adoption of Artificial Intelligence (AI) in the Canadian healthcare system falls behind that of other countries. Socio-technological considerations such as organizational readiness and a limited understanding of the technology are a few barriers ...

A Framework for Implementing Disease Prevention and Behavior Change Evidence at Scale.

Studies in health technology and informatics
The current corpus of evidence-based information for chronic disease prevention and treatment is vast and growing rapidly. Behavior change theories are increasingly more powerful but difficult to operationalize in the current healthcare system. Milli...

Federated Diabetes Prediction in Canadian Adults Using Real-world Cross-Province Primary Care Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Integrating Electronic Health Records (EHR) and the application of machine learning present opportunities for enhancing the accuracy and accessibility of data-driven diabetes prediction. In particular, developing data-driven machine learning models c...

From the Editors.

Healthcare quarterly (Toronto, Ont.)
There is no doubt that 2023 was a very difficult year for many Canadians, as well as people across the world. War caused massive upheaval globally, inflation continued to impose financial hardship on families and our health systems experienced anothe...

Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement from the ACR, CAR, ESR, RANZCR and RSNA.

Radiology. Artificial intelligence
Artificial Intelligence (AI) carries the potential for unprecedented disruption in radiology, with possible positive and negative consequences. The integration of AI in radiology holds the potential to revolutionize healthcare practices by advancing ...

Prior CT Improves Deep Learning for Malignancy Risk Estimation of Screening-detected Pulmonary Nodules.

Radiology
Background Prior chest CT provides valuable temporal information (eg, changes in nodule size or appearance) to accurately estimate malignancy risk. Purpose To develop a deep learning (DL) algorithm that uses a current and prior low-dose CT examinatio...

Morphologic clustering of earcanals using deep learning algorithm to design artificial ears dedicated to earplug attenuation measurement.

The Journal of the Acoustical Society of America
Designing earplugs adapted for the widest number of earcanals requires acoustical test fixtures (ATFs) geometrically representative of the population. Most existing ATFs are equipped with unique sized straight cylindrical earcanals, considered repres...

Deep learning using multilayer perception improves the diagnostic acumen of spirometry: a single-centre Canadian study.

BMJ open respiratory research
RATIONALE: Spirometry and plethysmography are the gold standard pulmonary function tests (PFT) for diagnosis and management of lung disease. Due to the inaccessibility of plethysmography, spirometry is often used alone but this leads to missed or mis...

Towards emotionally aligned social robots for dementia: perspectives of care partners and persons with dementia.

Alzheimer's & dementia : the journal of the Alzheimer's Association
BACKGROUND: Persons living with dementia and their care partners place a high value on aging in place and maintaining independence. Socially assistive robots - embodied characters or pets that provide companionship and aid through social interaction ...