Extraction, labelling, clustering, and semantic mapping of segments from clinical notes

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00209805%3A_____%2F23%3A00079390" target="_blank" >RIV/00209805:_____/23:00079390 - isvavai.cz</a>

Result on the web

<a href="https://pubmed.ncbi.nlm.nih.gov/37167037/" target="_blank" >https://pubmed.ncbi.nlm.nih.gov/37167037/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TNB.2023.3275195" target="_blank" >10.1109/TNB.2023.3275195</a>

Result language

angličtina

Original language name

Extraction, labelling, clustering, and semantic mapping of segments from clinical notes

Original language description

This work is motivated by the scarcity of tools for accurate, unsupervised information extraction from unstructured clinical notes in computationally underrepresented languages, such as Czech. We introduce a stepping stone to a broad array of downstream tasks such as summarisation or integration of individual patient records, extraction of structured information for national cancer registry reporting or building of semi-structured semantic patient representations that can be used for computing patient embeddings. More specifically, we present a method for unsupervised extraction of semantically-labelled textual segments from clinical notes and test it out on a dataset of Czech breast cancer patients, provided by Masaryk Memorial Cancer Institute (the largest Czech hospital specialising exclusively in oncology). Our goal was to extract, classify (i.e. label) and cluster segments of the free-text notes that correspond to specific clinical features (e.g., family background, comorbidities or toxicities). Finally, we propose a tool for computer-assisted semantic mapping of segment types to pre-defined ontologies and validate it on a downstream task of category-specific patient similarity. The presented results demonstrate the practical relevance of the proposed approach for building more sophisticated extraction and analytical pipelines deployed on Czech clinical notes.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

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

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

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

Name of the periodical

IEEE transactions on nanobioscience

ISSN

1536-1241

e-ISSN

1558-2639

Volume of the periodical

22

Issue of the periodical within the volume

4

Country of publishing house

US - UNITED STATES

Number of pages

8

Pages from-to

781-788

UT code for WoS article

001082250700011

EID of the result in the Scopus database

2-s2.0-85162886349