Analysis of Historical Medical Phenomena Using Large N-Gram Corpora

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14110%2F17%3A00113795" target="_blank" >RIV/00216224:14110/17:00113795 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.3233/978-1-61499-830-3-437" target="_blank" >http://dx.doi.org/10.3233/978-1-61499-830-3-437</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/978-1-61499-830-3-437" target="_blank" >10.3233/978-1-61499-830-3-437</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analysis of Historical Medical Phenomena Using Large N-Gram Corpora

Popis výsledku v původním jazyce

Historically, numerous indirect references to real world phenomena have been conserved in literature. High-quality libraries of digitized books and their derivatives (like the Google NGram Viewer) have proliferated. These tools simplify, the visualization of trends in phrase usage within the collective memory of language groups. A straightforward interpretation of these frequency changes is, however, too simplistic to draw conclusions about the underlying reality because it is affected by several sources of bias. Although these resources have been studied in social sciences and psychology, there is still lack of user-friendly, yet rigorous methods for analysis of phenomena relevant for medicine. We present a methodological framework to study relationships of observable phenomena quantitatively over periods, which span over centuries. We discuss its suitability for knowledge extraction from current and future large-scale, book-derived, n-gram collections.

Název v anglickém jazyce

Analysis of Historical Medical Phenomena Using Large N-Gram Corpora

Popis výsledku anglicky

Historically, numerous indirect references to real world phenomena have been conserved in literature. High-quality libraries of digitized books and their derivatives (like the Google NGram Viewer) have proliferated. These tools simplify, the visualization of trends in phrase usage within the collective memory of language groups. A straightforward interpretation of these frequency changes is, however, too simplistic to draw conclusions about the underlying reality because it is affected by several sources of bias. Although these resources have been studied in social sciences and psychology, there is still lack of user-friendly, yet rigorous methods for analysis of phenomena relevant for medicine. We present a methodological framework to study relationships of observable phenomena quantitatively over periods, which span over centuries. We discuss its suitability for knowledge extraction from current and future large-scale, book-derived, n-gram collections.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Medinfo 2017: Precision healthcare through informatics: proceedings of the 16th World Congress on Medical and Health Informatics

ISBN

9781614998297

ISSN

0926-9630

e-ISSN

—

Počet stran výsledku

5

Strana od-do

437-441

Název nakladatele

IOS PRESS

Místo vydání

AMSTERDAM

Místo konání akce

Xiamen

Datum konání akce

1. 1. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000449471200091