Matthew S. Simpson

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Memory access violations are a leading source of unreliability in C programs. As evidence of this problem, a variety of methods exist that retrofit C with software checks to detect memory errors at runtime. However, these methods generally suffer from one or more drawbacks including the inability to detect all errors, the use of incompatible metadata, the(More)
The biomedical community makes extensive use of text mining technology. In the past several years, enormous progress has been made in developing tools and methods, and the community has been witness to some exciting developments. Although the state of the community is regularly reviewed, the sheer volume of work related to biomedical text mining and the(More)
In making clinical decisions, physicians often seek out information about how to best care for their patients. Information relevant to a physician can be related to a variety of clinical tasks such as (i) determining a patient’s most likely diagnosis given a list of symptoms, (ii) determining if a particular test is indicated for a given situation, and(More)
Providing access to relevant biomedical literature in a clinical setting has the potential to bridge a critical gap in evidence-based medicine. Here, our goal is specifically to provide relevant articles to clinicians to improve their decision-making in diagnosing, treating, and testing patients. To this end, the TREC 2014 Clinical Decision Support Track(More)
Out-of-memory errors are a serious source of unreliability in most embedded systems [22]. Applications run out of main memory because of the frequent difficulty of estimating the memory requirement before deployment, either because it depends on input data, or because certain language features prevent estimation. The typical lack of disks and virtual memory(More)
Images are frequently used in articles to convey essential information in context with correlated text. However, searching images in a task-specific way poses significant challenges. To minimize limitations of low-level feature representations in content-based image retrieval (CBIR), and to complement text-based search, we propose a multi-modal image search(More)
PURPOSE Medical images are a significant information source for clinical decision-making. Currently available information retrieval and decision support systems rely primarily on the text of scientific publications to find evidence in support of clinical information needs. The images and illustrations are available only within the full text of a scientific(More)
Out-of-memory errors are a serious source of unreliability in most embedded systems. Applications run out of main memory because of the frequent difficulty of estimating the memory requirement before deployment, either because it depends on input data, or because certain language features prevent estimation. The typical lack of disks and virtual memory in(More)
The lack of virtual memory protection is a serious source of unreliability in many embedded systems. Without the segment-level protection it provides, these systems are subject to memory access violations, stemming from programmer error, whose results can be dangerous and catastrophic in safety-critical systems. The traditional method of testing embedded(More)
This article describes the participation of the Communications Engineering Branch (CEB), a division of the Lister Hill National Center for Biomedical Communications, in the ImageCLEF 2011 medical retrieval track. Our methods encompass a variety of techniques relating to textand content-based image retrieval. Our textual approaches primarily utilize the(More)