A review of alignment based similarity measures for web usage mining
AbstractIn order to understand web-based application user behavior, web usage mining applies unsupervised learning techniques to discover hidden patterns from web data that captures user browsing on...
View ArticleAccurate and interpretable evaluation of surgical skills from kinematic data...
AbstractPurposeManual feedback from senior surgeons observing less experienced trainees is a laborious task that is very expensive, time-consuming and prone to subjectivity. With the number of surgical...
View ArticleQuantitative CT Evidence of Airway Inflammation in WTC Workers and Volunteers...
AbstractBackgroundThe most common abnormal spirometric pattern reported in WTC worker and volunteer cohorts has consistently been that of a nonobstructive reduced forced vital capacity (low FVC). Low...
View ArticleKnowledge-Based Categorization of Scientific Articles for Similarity Predictions
AbstractStaying aware of new approaches emerging within specific areas can be challenging for researchers who have to follow many feeds such as journals articles, authors’ papers, and other basic...
View ArticleInceptionTime: Finding AlexNet for time series classification
AbstractThis paper brings deep learning at the forefront of research into time series classification (TSC). TSC is the area of machine learning tasked with the categorization (or labelling) of time...
View ArticleDeep Learning for Histopathological Image Analysis
AbstractAnatomical Pathology dates back to the nineteenth century when Rudolf Virchow introduced his concept of cellular pathology and when the technical improvements of light microscopy enabled...
View ArticleThe association of reduced left ventricular strains with increased...
AbstractBackgroundMyocardial fibrosis and left ventricular (LV) longitudinal strain are independently associated with adverse clinical outcomes. However, the relationship between tissue properties and...
View ArticleEnd-to-end deep representation learning for time series clustering: a...
AbstractTime series are ubiquitous in data mining applications. Similar to other types of data, annotations can be challenging to acquire, thus preventing from training time series classification...
View ArticleSmooth Perturbations for Time Series Adversarial Attacks
AbstractAdversarial attacks represent a threat to every deep neural network. They are particularly effective if they can perturb a given model while remaining undetectable. They have been initially...
View ArticleComparing left atrial indices by CMR in association with left ventricular...
AbstractLeft atrial (LA) features are altered when diastolic dysfunction (DD) is present. The relations of LA features to the DD severity and to adverse outcomes remain unclear using CMR images. We...
View ArticleData Augmentation for Time Series Classification with Deep Learning Models
AbstractDeep Learning models for time series classification are benchmarked on the UCR Archive. This archive contains 128 datasets. Unfortunately only 5 datasets contain more than 1000 training...
View ArticleEstimating time series averages from latent space of multi-tasking neural...
AbstractTime series averages are one key input to temporal data mining techniques such as classification, clustering, forecasting, etc. In practice, the optimality of estimated averages often impacts...
View ArticleEnhancing GNN Feature Modeling for Document Information Extraction Using...
AbstractBusiness documents are used every day by all kinds and sizes of companies and administrations, even if most of these entities have several information systems where the documents are...
View ArticleComparison between compressed sensing and segmented cine cardiac magnetic...
AbstractPurposeHighly accelerated compressed sensing cine has allowed for quantification of ventricular function in a single breath hold. However, compared to segmented breath hold techniques, there...
View ArticleAssociation of pulmonary transit time by cardiac magnetic resonance with...
AbstractBackgroundLonger pulmonary transit time (PTT) is closely associated with hemodynamic abnormalities. However, the implications on heart failure (HF) risk have not been investigated broadly in...
View ArticleTime series adversarial attacks: an investigation of smooth perturbations and...
AbstractAdversarial attacks represent a threat to every deep neural network. They are particularly effective if they can perturb a given model while remaining undetectable. They have been initially...
View ArticleUnderstanding fibrosis pathogenesis via modeling macrophage-fibroblast...
AbstractFibrosis is a progressive biological condition, leading to organ dysfunction in various clinical settings. Although fibroblasts and macrophages are known as key cellular players for fibrosis...
View ArticleShapeDBA: Generating Effective Time Series Prototypes Using ShapeDTW...
AbstractTime series data can be found in almost every domain, ranging from the medical field to manufacturing and wireless communication. Generating realistic and useful exemplars and prototypes is a...
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