Search Results - "R. Zaiane, Osmar"
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Exploring interpretable graph convolutional networks for autism spectrum disorder diagnosis
Published in International journal for computer assisted radiology and surgery (01-04-2023)“…Purpose Finding the biomarkers associated with autism spectrum disorder (ASD) is helpful for understanding the underlying roots of the disorder and can lead to…”
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Anomaly Detection in Resource Constrained Environments With Streaming Data
Published in IEEE transactions on emerging topics in computational intelligence (01-06-2022)“…Isolation Forest (or iForest ) is a well-known technique for anomaly detection. It is, however, a bulky approach that assumes the luxury of large storage space…”
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A Multi-Component Framework for the Analysis and Design of Explainable Artificial Intelligence
Published in Machine learning and knowledge extraction (01-12-2021)“…The rapid growth of research in explainable artificial intelligence (XAI) follows on two substantial developments. First, the enormous application success of…”
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Interdisciplinary-driven hypotheses on spatial associations of mixtures of industrial air pollutants with adverse birth outcomes
Published in Environment international (01-10-2019)“…Adverse birth outcomes (ABO) such as prematurity and small for gestational age confer a high risk of mortality and morbidity. ABO have been linked to air…”
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Educational data mining applications and tasks: A survey of the last 10 years
Published in Education and information technologies (2018)“…Educational Data Mining (EDM) is the field of using data mining techniques in educational environments. There exist various methods and applications in EDM…”
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Discovering co-location patterns with aggregated spatial transactions and dependency rules
Published in International journal of data science and analytics (01-03-2018)“…Co-location pattern mining focuses on finding associations among spatial features. Existing co-location pattern mining techniques mainly rely on frequency…”
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Modeling the dynamic brain network representation for autism spectrum disorder diagnosis
Published in Medical & biological engineering & computing (01-07-2022)“…The dynamic functional connectivity analysis provides valuable information for understanding functional brain activity underlying different cognitive…”
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Artificial intelligence enabled automated diagnosis and grading of ulcerative colitis endoscopy images
Published in Scientific reports (17-02-2022)“…Endoscopic evaluation to reliably grade disease activity, detect complications including cancer and verification of mucosal healing are paramount in the care…”
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A Collaborative Self-Supervised Domain Adaptation for Low-Quality Medical Image Enhancement
Published in IEEE transactions on medical imaging (01-07-2024)“…Medical image analysis techniques have been employed in diagnosing and screening clinical diseases. However, both poor medical image quality and illumination…”
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Collaborative learning of graph generation, clustering and classification for brain networks diagnosis
Published in Computer methods and programs in biomedicine (01-06-2022)“…•We develop a supervised multi-graph clustering for removing the noisy functional connections from the group level and identifying the critical graph…”
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WS-LungNet: A two-stage weakly-supervised lung cancer detection and diagnosis network
Published in Computers in biology and medicine (01-03-2023)“…Computer-aided lung cancer diagnosis (CAD) system on computed tomography (CT) helps radiologists guide preoperative planning and prognosis assessment. The…”
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Image Quality Assessment Guided Collaborative Learning of Image Enhancement and Classification for Diabetic Retinopathy Grading
Published in IEEE journal of biomedical and health informatics (01-03-2023)“…Diabetic retinopathy (DR) is one of the most serious complications of diabetes and is a prominent cause of permanent blindness. However, the low-quality fundus…”
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13
BrainTGL: A dynamic graph representation learning model for brain network analysis
Published in Computers in biology and medicine (01-02-2023)“…Modeling the dynamics characteristics in functional brain networks (FBNs) is important for understanding the functional mechanism of the human brain. However,…”
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14
Modeling global and local label correlation with graph convolutional networks for multi-label chest X-ray image classification
Published in Medical & biological engineering & computing (01-09-2022)“…The diagnosis of chest diseases is a challenging task for assessing thousands of radiology subjects. Their diagnosis decisions heavily rely on the expert…”
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15
BrainDAS: Structure-aware domain adaptation network for multi-site brain network analysis
Published in Medical image analysis (01-08-2024)“…In the medical field, datasets are mostly integrated across sites due to difficult data acquisition and insufficient data at a single site. The domain shift…”
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Graph Self-supervised Learning with Application to Brain Networks Analysis
Published in IEEE journal of biomedical and health informatics (01-08-2023)“…The less training data and insufficient supervision limit the performance of the deep supervised models for brain disease diagnosis. It is significant to…”
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Exploiting task relationships for Alzheimer’s disease cognitive score prediction via multi-task learning
Published in Computers in biology and medicine (01-01-2023)“…Alzheimer’s disease (AD) is highly prevalent and a significant cause of dementia and death in elderly individuals. Motivated by breakthroughs of multi-task…”
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18
Lesion-aware knowledge distillation for diabetic retinopathy lesion segmentation
Published in Applied intelligence (Dordrecht, Netherlands) (2024)“…Retinal fundus images have been widely utilized for screening Diabetic Retinopathy (DR). The lesion information contained in these images is indispensable for…”
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Extracellular Proteomes of Arabidopsis Thaliana and Brassica Napus Roots: Analysis and Comparison by MudPIT and LC-MS/MS
Published in Plant and soil (01-08-2006)“…An important principle of the functional organization of plant cells is the targeting of proteins to specific subcellular locations. The physical location of…”
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Depression symptoms modelling from social media text: an LLM driven semi-supervised learning approach
Published in Language resources and evaluation (01-09-2024)“…A fundamental component of user-level social media language based clinical depression modelling is depression symptoms detection (DSD). Unfortunately, there…”
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