The next cohort of our program, designed to empower policy professionals with a comprehensive understanding of AI, will take place in Ottawa on November 28 and 29.
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Publications
Automated liver segmentation and steatosis grading using deep learning on B-mode ultrasound images
Early detection of nonalcoholic fatty liver disease (NAFLD) is crucial to avoid further complications. Ultrasound is often used for screenin… (see more)g and monitoring of hepatic steatosis, however it is limited by the subjective interpretation of images. Computer assisted diagnosis could aid radiologists to achieve objective grading, and artificial intelligence approaches have been tested across various medical applications. In this study, we evaluated the performance of a two-stage hepatic steatosis detection deep learning framework, with a first step of liver segmentation and a subsequent step of hepatic steatosis classification. We evaluated the models on internal and external datasets, aiming to understand the generalizability of the framework. In the external dataset, our segmentation model achieved a Dice score of 0.92 (95% CI: 0.78, 1.00), and our classification model achieved an area under the receiver operating characteristic curve of 0.84 (95% CI: 0.79, 0.89). Our findings highlight the potential benefits of applying artificial intelligence models in NAFLD assessment.
124 Development of a Novel Dosimetry Software for Patient-Specific Intravascular Brachytherapy Treatment Planning on Optical Coherence Tomography Images
256 Patient-Specific Pre-Treatment Nuclei Size Distribution is of Significance for Post Radiation Therapy Locoregional Recurrence and Survival Outcomes
Impact of a vaccine passport on first-dose SARS-CoV-2 vaccine coverage by age and area-level social determinants of health in the Canadian provinces of Quebec and Ontario: an interrupted time series analysis