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HTP-NLP: A New NLP System for High Throughput Phenotyping
2017Secondary use of clinical data for research requires a method to quickly process the data so that researchers can quickly extract cohorts. We present two advances in the High Throughput Phenotyping NLP system which support the aim of truly high throughput processing of clinical data, inspired by a characterization of the linguistic properties of such ...
Daniel R, Schlegel +3 more
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2017
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NLP-???????????????? ?????? EDL-?????????? ???????????????????????? ??????????????????????????
2020?????????????????????????????? ???????????? ?????????????????????? ???????????????? ?????????????????????????? ?? ?????????????????????????? ???? ???????????????????? ?????????????????? ?????????????????? ???????????????????????? ?????? ???????? ???????????????????? ?????????????? ???????????? ?????????????????? ??????????????: ???????????????? ????????
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2017
The maximum entropy linear programming problem in primal and dual formulations is considered. The results of computational experiments with the NEOS-solvers for nonlinear programming problems are reported for both formulations. The computational experiments with solving the dual problem using Shor's r-algorithm with an adaptive step are discussed.
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The maximum entropy linear programming problem in primal and dual formulations is considered. The results of computational experiments with the NEOS-solvers for nonlinear programming problems are reported for both formulations. The computational experiments with solving the dual problem using Shor's r-algorithm with an adaptive step are discussed.
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Using NLP or NLP Resources for Information Retrieval Tasks
1999The impact of NLP on information retrieval tasks has largely been one of promise rather than substance. While there are exceptions to this as some of the chapters in the present volume demonstrate, for the most part NLP and information retrieval have only recently started to dovetail together. In this chapter we will present a precis of our experiments
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