EasyNER: A Customizable and Easy-to-Use Pipeline for Deep Learning- and Dictionary-based Named Entity Recognition from Medical Text [Software]
Ahmed, Rafsan LU
; Aits, Sonja
LU
; Kazemi Rashed, Salma
LU
; Nugues, Pierre
LU
; Lamarca, Antton
LU
; Berntsson, Peter
; Skafte, Alexander
; Klang, Marcus
LU
; Olde, Ola
and Barvesten, Adam
, et al.
(2024)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/7bb7d0d3-8de0-470f-9508-aac070da477e
- author
- Ahmed, Rafsan
LU
; Aits, Sonja
LU
; Kazemi Rashed, Salma
LU
; Nugues, Pierre
LU
; Lamarca, Antton
LU
; Berntsson, Peter
; Skafte, Alexander
; Klang, Marcus
LU
; Olde, Ola
and Barvesten, Adam
, et al. (More)
- Ahmed, Rafsan
LU
; Aits, Sonja
LU
; Kazemi Rashed, Salma
LU
; Nugues, Pierre
LU
; Lamarca, Antton
LU
; Berntsson, Peter
; Skafte, Alexander
; Klang, Marcus
LU
; Olde, Ola
; Barvesten, Adam
and Lindholm, William
(Less)
- organization
-
- Cell Death, Lysosomes and Artificial Intelligence (research group)
- LTH Profile Area: Engineering Health
- LU Profile Area: Natural and Artificial Cognition
- BECC: Biodiversity and Ecosystem services in a Changing Climate
- LU Profile Area: Proactive Ageing
- LU Profile Area: Nature-based future solutions
- LTH Profile Area: AI and Digitalization
- EpiHealth: Epidemiology for Health
- LUCC: Lund University Cancer Centre
- eSSENCE: The e-Science Collaboration
- Robotics and Semantic Systems
- Hematogenomics (research group)
- Division of Hematology and Clinical Immunology
- publishing date
- 2024-04-02
- type
- Non-textual form
- publication status
- published
- subject
- keywords
- artificial intelligence, deep learning, natural language processing, dictionaries, software, text mining, named entity recognition, data science, PubMed
- publisher
- Code Ocean
- DOI
- 10.24433/CO.6908880.v1
- project
- Lund University AI Research
- LU Land
- Studying COVID-19 with artificial intelligence
- Lysosomes in cell death - from molecular mechanisms to new treatment strategies
- Biomaterials@LU
- Revealing drivers of cell death disruption across species and theri links to biodiversity loss and human disease
- Biomedical text mining for systems biology
- The Swedish Centre of Excellence on Impacts of Climate Extremes (Climes)
- language
- English
- LU publication?
- yes
- id
- 7bb7d0d3-8de0-470f-9508-aac070da477e
- alternative location
- https://github.com/Aitslab/EasyNER
- date added to LUP
- 2024-12-13 12:40:39
- date last changed
- 2026-01-15 08:50:54
@misc{7bb7d0d3-8de0-470f-9508-aac070da477e,
author = {{Ahmed, Rafsan and Aits, Sonja and Kazemi Rashed, Salma and Nugues, Pierre and Lamarca, Antton and Berntsson, Peter and Skafte, Alexander and Klang, Marcus and Olde, Ola and Barvesten, Adam and Lindholm, William}},
keywords = {{artificial intelligence; deep learning; natural language processing; dictionaries; software; text mining; named entity recognition; data science; PubMed}},
language = {{eng}},
month = {{04}},
publisher = {{Code Ocean}},
title = {{EasyNER: A Customizable and Easy-to-Use Pipeline for Deep Learning- and Dictionary-based Named Entity Recognition from Medical Text [Software]}},
url = {{http://dx.doi.org/10.24433/CO.6908880.v1}},
doi = {{10.24433/CO.6908880.v1}},
year = {{2024}},
}