AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Ontario

Showing 31 to 40 of 43 articles

Clear Filters

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...

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...

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 ...

Identifying drugs with disease-modifying potential in Parkinson's disease using artificial intelligence and pharmacoepidemiology.

Pharmacoepidemiology and drug safety
PURPOSE: The aim of the study was to assess the feasibility of an approach combining computational methods and pharmacoepidemiology to identify potentially disease-modifying drugs in Parkinson's disease (PD).

Measuring Boards Using Quantitative Tools from Natural Language Processing.

Healthcare quarterly (Toronto, Ont.)
Natural language processing (NLP) tools provide quantitative methods to analyze board minutes and better understand and measure the work of the board. Techniques such as riverbed graphs and sentiment analysis provide objective, measurable information...

Conditionally positive: a qualitative study of public perceptions about using health data for artificial intelligence research.

BMJ open
OBJECTIVES: Given widespread interest in applying artificial intelligence (AI) to health data to improve patient care and health system efficiency, there is a need to understand the perspectives of the general public regarding the use of health data ...

Can machine learning optimize the efficiency of the operating room in the era of COVID-19?

Canadian journal of surgery. Journal canadien de chirurgie
The cancellation of large numbers of surgical procedures because of the coronavirus disease 2019 (COVID-19) pandemic has drastically extended wait lists and negatively affected patient care and experience. As many facilities resume clinical work owin...

Application of machine learning to identify predators of stocked fish in Lake Ontario: using acoustic telemetry predation tags to inform management.

Journal of fish biology
Understanding predator-prey interactions and food web dynamics is important for ecosystem-based management in aquatic environments, as they experience increasing rates of human-induced changes, such as the addition and removal of fishes. To quantify ...