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Articles 1 - 2 of 2
Full-Text Articles in Medicine and Health Sciences
Bayesian Methods For Graphical Models With Neighborhood Selection., Sagnik Bhadury
Bayesian Methods For Graphical Models With Neighborhood Selection., Sagnik Bhadury
Electronic Theses and Dissertations
Graphical models determine associations between variables through the notion of conditional independence. Gaussian graphical models are a widely used class of such models, where the relationships are formalized by non-null entries of the precision matrix. However, in high-dimensional cases, covariance estimates are typically unstable. Moreover, it is natural to expect only a few significant associations to be present in many realistic applications. This necessitates the injection of sparsity techniques into the estimation method. Classical frequentist methods, like GLASSO, use penalization techniques for this purpose. Fully Bayesian methods, on the contrary, are slow because they require iteratively sampling over a quadratic …
Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche
Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche
Electronic Theses and Dissertations
The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous …