Speaker Series: Machine Learning in Health

Cynthia Lokker

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Using artificial intelligence to accelerate your review process


Candyce Hamel is a Senior Epidemiologist with the Canadian Association of Radiologists. Her research interests include the use of artificial intelligence in evidence reviews and evidence review methodology. 

Description of Candyce Hamel's talk:

Systematic reviews are the cornerstone of evidence-based medicine, supporting clinical decision-making, such as through use in guidelines, and informing policy decisions. However, they are time-consuming and resource intensive, and there is growing demand by stakeholders to produce evidence more quickly, while still maintaining robust methods. Screening the citation yields from electronic databases often account for a large part of the review process. Artificial intelligence (AI), more specifically active machine learning (AML), has emerged in the past decade, and has been integrated in several systematic review software applications.

The use of AI may offer potential gains relevant to stakeholders and research teams that include more timely production/delivery of preliminary findings, more efficient use of team member skills, and reduction of screening burden. Many researchers may be interested by the premise of using AI, but are uncertain as to its validity and means for operationalization. In this presentation, we will provide some guidance and considerations on how you can integrate AI and AML into your review process.

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