Samuel Bayer

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We describe MITRE’s two submissions to the RTE Challenge, intended to exemplify two different ends of the spectrum of possibilities. The first submission is a traditional system based on linguistic analysis and inference, while the second is inspired by alignment approaches from machine translation. We also describe our efforts to build our own entailment(More)
PURPOSE Medical records must often be stripped of patient identifiers, or de-identified, before being shared. De-identification by humans is time-consuming, and existing software is limited in its generality. The open source MITRE Identification Scrubber Toolkit (MIST) provides an environment to support rapid tailoring of automated de-identification to(More)
OBJECTIVE De-identified medical records are critical to biomedical research. Text de-identification software exists, including "resynthesis" components that replace real identifiers with synthetic identifiers. The goal of this research is to evaluate the effectiveness and examine possible bias introduced by resynthesis on de-identification software. (More)
PURPOSE We describe an experiment to build a de-identification system for clinical records using the open source MITRE Identification Scrubber Toolkit (MIST). We quantify the human annotation effort needed to produce a system that de-identifies at high accuracy. METHODS Using two types of clinical records (history and physical notes, and social work(More)
We describe a novel method for detecting errors in task-based human-computer (HC) dialogues by automatically deriving them from semantic tags. We examined 27 HC dialogues from the DARPA Communicator air travel domain, comparing user inputs to system responses to look for slot value discrepancies, both automatically and manually. For the automatic method, we(More)
In this paper, we will describe work in progress at the MITRE Corporation on embedding speech-enabled interfaces in Web browsers. This research is part of our work to establish the infrastructure to create Web-hosted versions of prototype multimodal interfaces, both intelligent and otherwise. Like many others, we believe that the Web is the best potential(More)
communications (HPCC) technology . The user environment for this project is K-12 education , which offers a range of electronically connecte d users with a rich variety of uses . AskERIC, one o f the project's research partners, currently provides a Smithsonian award-nominated questionanswerin g service to K-12 educators through the Internet vi a expert(More)
To support engaging human users in robust, mixed-initiative speech dialogue interactions which reach beyond current capabilities in dialogue systems, the DARPA Communicator program [1] is funding the development of a distributed message-passing infrastructure for dialogue systems which all Communicator participants are using. In this presentation, we(More)
OBJECTIVE Secondary use of clinical text is impeded by a lack of highly effective, low-cost de-identification methods. Both, manual and automated methods for removing protected health information, are known to leave behind residual identifiers. The authors propose a novel approach for addressing the residual identifier problem based on the theory of Hiding(More)