119 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of OttawaCA7 papers
- Charité - Universitätsmedizin BerlinDE3 papers
- Carleton UniversityCA2 papers
- Hebrew University of JerusalemIL2 papers
- McMaster UniversityCA2 papers
- Ottawa HospitalCA2 papers
- Ottawa Hospital Research InstituteCA2 papers
- Tel Aviv Sourasky Medical CenterIL2 papers
- Tel Aviv UniversityIL2 papers
- Aarhus University HospitalDK1 paper
- Academic College of Tel Aviv-YafoIL1 paper
- Agricultural Research Institute of OntarioCA1 paper
10 papers
AI for pRedicting Exacerbations in KIDs with aSthma (AIRE-KIDS)
Hui-Lee Ooi, Nicholas Mitsakakis, Margerie Huet Dastarac +5
Recurrent exacerbations remain a common yet preventable outcome for many children with asthma. Machine learning (ML) algorithms using electronic medical records (EMR) could allow a…
Transfer Learning and Machine Learning for Training Five Year Survival Prognostic Models in Early Breast Cancer
Lisa Pilgram, Kai Yang, Ana-Alicia Beltran-Bless +22
Prognostic information is essential for decision-making in breast cancer management. Recently trials have predominantly focused on genomic prognostication tools, even though clinic…
A Consensus Privacy Metrics Framework for Synthetic Data
Lisa Pilgram, Fida K. Dankar, Jorg Drechsler +12
Synthetic data generation is one approach for sharing individual-level data. However, to meet legislative requirements, it is necessary to demonstrate that the individuals' privacy…
KMT2B-related disorders: expansion of the phenotypic spectrum and long-term efficacy of deep brain stimulation
L Cif, D Demailly, JP Lin +112
Heterozygous mutations in KMT2B are associated with an early-onset, progressive, and often complex dystonia (DYT28). Key characteristics of typical disease include focal motor feat…
Synthetic Data Generation for Augmenting Small Samples
Dan Liu, Samer El Kababji, Nicholas Mitsakakis +6
Small datasets are common in health research. However, the generalization performance of machine learning models is suboptimal when the training datasets are small. To address this…
Under the Cover Infant Pose Estimation using Multimodal Data
Daniel G. Kyrollos, Anthony Fuller, Kim Greenwood +2
Infant pose monitoring during sleep has multiple applications in both healthcare and home settings. In a healthcare setting, pose detection can be used for region of interest detec…
Partial annotations for the segmentation of large structures with low annotation cost
Bella Specktor Fadida, Daphna Link Sourani, Liat Ben Sira Elka Miller +2
Deep learning methods have been shown to be effective for the automatic segmentation of structures and pathologies in medical imaging. However, they require large annotated dataset…
Automatic linear measurements of the fetal brain on MRI with deep neural networks
Netanell Avisdris, Bossmat Yehuda, Ori Ben-Zvi +6
Timely, accurate and reliable assessment of fetal brain development is essential to reduce short and long-term risks to fetus and mother. Fetal MRI is increasingly used for fetal b…
Measuring uncertainty during respiratory rate estimation using pressure-sensitive mats
S. Nizami, A. Bekele, M. Hozayen +3
We develop and evaluate a respiratory rate estimation algorithm that utilizes data from pressure-sensitive mat (PSM) technology for continuous patient monitoring in neonatal intens…
YOURPRIVACYPROTECTOR, A recommender system for privacy settings in social networks
Kambiz Ghazinour, Stan Matwin, Marina Sokolova
Ensuring privacy of users of social networks is probably an unsolvable conundrum. At the same time, an informed use of the existing privacy options by the social network participan…