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All tools in the DAVID Bioinformatics Resources aim to provide functional interpretation of large lists of genes derived from genomic studies. The newly updated DAVID Bioinformatics Resources consists of the DAVID Knowledgebase and five integrated, web-based functional annotation tool suites: the DAVID Gene Functional Classification Tool, the DAVID(More)
In computer vision, the bag-of-visual words image representation has been shown to yield good results. Recent work has shown that modeling the spatial relationship between visual words further improves performance. Previous work extracts higher-order spatial features exhaustively. However, these spatial features are expensive to compute. We propose a novel(More)
BACKGROUND Due to the complex and distributed nature of biological research, our current biological knowledge is spread over many redundant annotation databases maintained by many independent groups. Analysts usually need to visit many of these bioinformatics databases in order to integrate comprehensive annotation information for their genes, which becomes(More)
Lymph nodes are assessed routinely in clinical practice and their size is followed throughout radiation or chemotherapy to monitor the effectiveness of cancer treatment. This paper presents a robust learning-based method for automatic detection and segmentation of solid lymph nodes from CT data, with the following contributions. First, it presents a(More)
This paper describes a software framework for the development of a ubiquitous computing environment for distributed engineering information services. Two fundamental issues are addressed: universal accessibility from devices to information services, and collaboration among the parties accessing the information services. The first issue calls for the(More)
BACKGROUND In a full-scale anesthesia simulator study we examined the relative effectiveness of advanced auditory displays for respiratory and blood pressure monitoring and of head-mounted displays (HMDs) as supplements to standard intraoperative monitoring. METHODS Participants were 16 residents and attendings. While performing a reading-based distractor(More)
A fundamental issue in multiple landmark detection is the reduction of computational cost. This problem has previously been addressed mainly by reducing the complexity of each individual landmark detector. We address the problem by optimizing the search strategy of multiple landmarks. When the relative positions of landmarks are constrained , the search(More)
We propose a novel method for removing irrelevant frames from a video given user-provided frame-level labeling for a very small number of frames. We first hypothesize a number of windows which possibly contain the object of interest, and then determine which window(s) truly contain the object of interest. Our method enjoys several favorable properties.(More)
Topic models from the text understanding literature have shown promising results in unsupervised image categoriza-tion and object localization. Categories are treated as topics , and words are formed by vector quantizing local de-scriptors of image patches. Limitations of topic models include their weakness in localizing objects, and the requirement of a(More)