Full text
Preview |
PDF
- Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (619kB) | Preview |
Clinical narrative analytics challenges
Citation
Menasalvas Ruiz, Ernestina 
ORCID: https://orcid.org/0000-0002-5615-6798, Rodríguez González, Alejandro ORCID: https://orcid.org/0000-0001-8801-4762, Costumero Moreno, Roberto ORCID: https://orcid.org/0000-0002-0069-5960, Ambit Hernández, Héctor and Gonzalo Martín, Consuelo ORCID: https://orcid.org/0000-0002-0804-9293
(2016).
Clinical narrative analytics challenges.
"Lecture Notes in Artificial Intelligence", v. 9920
;
pp. 23-32.
ISSN 0302-9743.
https://doi.org/10.1007/978-3-319-47160-0_2.
Description
| Title: | Clinical narrative analytics challenges |
|---|---|
| Author/s: |
|
| Item Type: | Article |
| Título de Revista/Publicación: | Lecture Notes in Artificial Intelligence |
| Date: | 2016 |
| ISSN: | 0302-9743 |
| Volume: | 9920 |
| Subjects: | |
| Freetext Keywords: | Clinical narratives; Natural language processing |
| Faculty: | E.T.S. de Ingenieros Informáticos (UPM) |
| Department: | Lenguajes y Sistemas Informáticos e Ingeniería del Software |
| Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
Abstract
Precision medicine or evidence based medicine is based on
the extraction of knowledge from medical records to provide individuals
with the appropriate treatment in the appropriate moment according to
the patient features. Despite the efforts of using clinical narratives for
clinical decision support, many challenges have to be faced still today
such as multilinguarity, diversity of terms and formats in different services,
acronyms, negation, to name but a few. The same problems exist
when one wants to analyze narratives in literature whose analysis would
provide physicians and researchers with highlights. In this talk we will
analyze challenges, solutions and open problems and will analyze several
frameworks and tools that are able to perform NLP over free text to
extract medical entities by means of Named Entity Recognition process.
We will also analyze a framework we have developed to extract and validate
medical terms. In particular we present two uses cases: (i) medical
entities extraction of a set of infectious diseases description texts provided
by MedlinePlus and (ii) scales of stroke identification in clinical
narratives written in Spanish.
More information
| Item ID: | 47992 |
|---|---|
| DC Identifier: | https://oa.upm.es/47992/ |
| OAI Identifier: | oai:oa.upm.es:47992 |
| DOI: | 10.1007/978-3-319-47160-0_2 |
| Official URL: | https://link.springer.com/chapter/10.1007%2F978-3-... |
| Deposited by: | Memoria Investigacion |
| Deposited on: | 06 Nov 2017 08:44 |
| Last Modified: | 03 Jun 2019 11:37 |
