Understanding Health Records in West Slavic Languages: Available Resources, Case Study in Oncology

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00131436" target="_blank" >RIV/00216224:14330/23:00131436 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.3233/SHTI230433" target="_blank" >http://dx.doi.org/10.3233/SHTI230433</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/SHTI230433" target="_blank" >10.3233/SHTI230433</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Understanding Health Records in West Slavic Languages: Available Resources, Case Study in Oncology

Popis výsledku v původním jazyce

Currently, there is very little research aimed at developing medical knowledge extraction tools for major West Slavic languages (Czech, Polish, and Slovak). This project lays the groundwork for a general medical knowledge extraction pipeline, introducing the resource vocabularies available for the respective languages (UMLS resources, ICD-10 translations and national drug databases). It demonstrates the utility of this approach on a case study using a large proprietary corpus of Czech oncology records consisting of more than 40 million words written about more than 4,000 patients. After correlating MedDRA terms found in patients' records with drugs prescribed to them, significant non-obvious associations were found between selected medical conditions being mentioned and the probability of certain drugs being prescribed over the course of the patient's treatment, in some cases increasing the probability of prescriptions by over 250%. This direction of research, producing large amounts of annotated data, is a prerequisite for training deep learning models and predictive systems.

Název v anglickém jazyce

Understanding Health Records in West Slavic Languages: Available Resources, Case Study in Oncology

Popis výsledku anglicky

Currently, there is very little research aimed at developing medical knowledge extraction tools for major West Slavic languages (Czech, Polish, and Slovak). This project lays the groundwork for a general medical knowledge extraction pipeline, introducing the resource vocabularies available for the respective languages (UMLS resources, ICD-10 translations and national drug databases). It demonstrates the utility of this approach on a case study using a large proprietary corpus of Czech oncology records consisting of more than 40 million words written about more than 4,000 patients. After correlating MedDRA terms found in patients' records with drugs prescribed to them, significant non-obvious associations were found between selected medical conditions being mentioned and the probability of certain drugs being prescribed over the course of the patient's treatment, in some cases increasing the probability of prescriptions by over 250%. This direction of research, producing large amounts of annotated data, is a prerequisite for training deep learning models and predictive systems.

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

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název statě ve sborníku

Healthcare Transformation with Informatics and Artificial Intelligence

ISBN

9781643684000

ISSN

0926-9630

e-ISSN

—

Počet stran výsledku

5

Strana od-do

97-101

Název nakladatele

IOS Press

Místo vydání

Amsterdam

Místo konání akce

Amsterdam

Datum konání akce

1. 1. 2023

Typ akce podle státní příslušnosti

CST - Celostátní akce

Kód UT WoS článku

—