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Multiview clustering is a framework for grouping objects given multiple views, e.g. text and image views describing the same set of entities. This paper introduces co-regularization techniques for multiview clustering that explicitly minimize a weighted sum of divergences to impose coherence between per-view learned models. Specifically, we iteratively minimize a weighted sum of divergences between...
We propose a novel approach for simultaneous exploratory analysis and prognosis of multiple chronic conditions that can enable healthcare professionals to harness the vast amounts of medical data available in electronic health records (EHRs) in a comprehensive manner for early treatment, the discovery of previously unknown symptoms and exploration of new associations in the context of individual chronic...
With vast amount of medical records being digitized in recent years in the form of Electronic Health Records (EHRs), accurate and large scale automated prognosis of diseases has become a possibility. However, most existing works in disease prediction have focused on a single condition or a few related conditions. Such models do not account for the fact that multiple conditions may co-occur in patients...
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