Emily Kawaler

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We consider the task of predicting which patients are most at risk for post-hospitalization venothromboembolism (VTE) using information automatically elicited from an EHR. Given a set of cases and controls, we use machine-learning methods to induce models for making these predictions. Our empirical evaluation of this approach offers a number of interesting(More)
While mechanisms exist to evaluate the user-perceived quality of video streamed over computer networks, there are few good mechanisms to do so in real time. In this paper, we evaluate the feasibility of predicting the stream quality of partial portions of a video stream based on either complete or incomplete information from previously rated streams. Using(More)
Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated(More)
In this study, the tail muscle microbiota of pacific white shrimp (Litopenaeus vannamei) sourced from five countries across Central and South America and Southeast Asia were determined and compared. The genomic DNA was sequenced at around 10 × coverage for each geographical location and was assembled de novo for comparative analysis. The assembled sequences(More)
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