Negation’s Not Solved: Generalizability Versus Optimizability in Clinical Natural Language Processing

A review of published work in clinical natural language processing (NLP) may suggest that the negation detection task has been “solved.” This work proposes that an optimizable solution does not equal a generalizable solution. We introduce a new machine learning-based Polarity Module for detecting negation in clinical text, and extensively compare its performance across domains. Using four manually annotated corpora of clinical text, we show that negation detection performance suffers when there is no in-domain development (for manual methods) or training data (for machine learning-based methods). Various factors (e.g., annotation guidelines, named entity characteristics, the amount of data, and lexical and syntactic context) play a role in making generalizability difficult, but none completely explains the phenomenon. Furthermore, generalizability remains challenging because it is unclear whether to use a single source for accurate data, combine all sources into a single model, or apply domain adaptation methods. The most reliable means to improve negation detection is to manually annotate in-domain training data (or, perhaps, manually modify rules); this is a strategy for optimizing performance, rather than generalizing it. These results suggest a direction for future work in domain-adaptive and task-adaptive methods for clinical NLP

A common type system for clinical natural language processing

Background: One challenge in reusing clinical data stored in electronic medical records is that these data are heterogenous. Clinical Natural Language Processing (NLP) plays an important role in transforming information in clinical text to a standard representation that is comparable and interoperable. Information may be processed and shared when a type system specifies the allowable data structures. Therefore, we aim to define a common type system for clinical NLP that enables interoperability between structured and unstructured data generated in different clinical settings. Results: We describe a common type system for clinical NLP that has an end target of deep semantics based on Clinical Element Models (CEMs), thus interoperating with structured data and accommodating diverse NLP approaches. The type system has been implemented in UIMA (Unstructured Information Management Architecture) and is fully functional in a popular open-source clinical NLP system, cTAKES (clinical Text Analysis and Knowledge Extraction System) versions 2.0 and later. Conclusions: We have created a type system that targets deep semantics, thereby allowing for NLP systems to encapsulate knowledge from text and share it alongside heterogenous clinical data sources. Rather than surface semantics that are typically the end product of NLP algorithms, CEM-based semantics explicitly build in deep clinical semantics as the point of interoperability with more structured data types

Corrupción y gestión migratoria en el México posrevolucionario

This work studies the nature, extension and significances of the corruption practices inside the Mexican Migration Service during the first decades of the 20th century. In a context in which the need to enter or exit the country was seen, both by Mexicans or foreigners, as an opportunity for illicit enrichment, the article reveals how corruption practices flourished under the increase of immigration regulations. The pervasiveness of these practices allows one to assess them as a consubstantial part of the political order as opposed to an issue of a moral character.En este trabajo se estudia la naturaleza, extensión y significados de prácticas de corrupción en el Servicio de Migración de México durante las primeras décadas del siglo XX. Se advierten las maneras en que la corrupción creció al amparo de un ensanchamiento de las regulaciones migratorias y el control fronterizo, en un contexto en que la necesidad de ingresar o salir de país por parte de extranjeros y mexicanos era valorada como una oportunidad para enriquecimientos ilícitos. La dimensión alcanzada por estas prácticas permite valorarlas como parte consustancial del orden político antes que como un asunto de carácter moral

An analysis of the influences on Appleton East High School technology education students' perception of the construction industry

Includes bibliographical references

Teaching language through theme building : a summary of project and materials : [an honors thesis] (HONRS 499)

There is no abstract available for this thesis.Honors CollegeThesis (B.?.

Alkaline rechargeable zinc/air battery

The research and development of a durable, elec. rechargeable Zn/O2 battery in the PSI-BEW project at the Paul Scherrer Institute is described in a review with many refs. The first phase included the development of La0.6Ca0.4CoO3-activated bifunctional O2 diffusion electrodes and zinc paste electrodes. The second phase included the optimization of the zinc paste electrode to improve the available capacity and peak power of the battery system. Based on the mass of the cell components, a specific peak power of 275 W/kg with O2 and 200 W/kg with air was calcd. for complete batteries. In collaboration with the Federal Institute of Technol., Lausanne, Switzerland, a bipolar filter-press type elec. rechargeable Zn/O2 battery delivering a peak power of ca. 100 W has been developed. The current-potential behavior was detd. as a function of the no. of bipolar cells (max. of 7), and the max. discharge capacity was detd. at different discharge rates. [on SciFinder (R)