[HTML][HTML] Clinical information extraction applications: a literature review

Y Wang, L Wang, M Rastegar-Mojarad, S Moon… - Journal of biomedical …, 2018 - Elsevier
Background With the rapid adoption of electronic health records (EHRs), it is desirable to
harvest information and knowledge from EHRs to support automated systems at the point of …

Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review

TA Koleck, C Dreisbach, PE Bourne… - Journal of the American …, 2019 - academic.oup.com
Objective Natural language processing (NLP) of symptoms from electronic health records
(EHRs) could contribute to the advancement of symptom science. We aim to synthesize the …

2018 n2c2 shared task on adverse drug events and medication extraction in electronic health records

S Henry, K Buchan, M Filannino… - Journal of the …, 2020 - academic.oup.com
Objective This article summarizes the preparation, organization, evaluation, and results of
Track 2 of the 2018 National NLP Clinical Challenges shared task. Track 2 focused on …

A survey on recent named entity recognition and relationship extraction techniques on clinical texts

P Bose, S Srinivasan, WC Sleeman IV, J Palta… - Applied Sciences, 2021 - mdpi.com
Significant growth in Electronic Health Records (EHR) over the last decade has provided an
abundance of clinical text that is mostly unstructured and untapped. This huge amount of …

The evidence for saturated fat and for sugar related to coronary heart disease

JJ DiNicolantonio, SC Lucan, JH O'Keefe - Progress in cardiovascular …, 2016 - Elsevier
Dietary guidelines continue to recommend restricting intake of saturated fats. This
recommendation follows largely from the observation that saturated fats can raise levels of …

Information extraction from electronic medical documents: state of the art and future research directions

MY Landolsi, L Hlaoua, L Ben Romdhane - Knowledge and Information …, 2023 - Springer
In the medical field, a doctor must have a comprehensive knowledge by reading and writing
narrative documents, and he is responsible for every decision he takes for patients …

In-boxbart: Get instructions into biomedical multi-task learning

M Parmar, S Mishra, M Purohit, M Luo… - arXiv preprint arXiv …, 2022 - arxiv.org
Single-task models have proven pivotal in solving specific tasks; however, they have
limitations in real-world applications where multi-tasking is necessary and domain shifts are …

[HTML][HTML] Annotating longitudinal clinical narratives for de-identification: The 2014 i2b2/UTHealth corpus

A Stubbs, Ö Uzuner - Journal of biomedical informatics, 2015 - Elsevier
Abstract The 2014 i2b2/UTHealth natural language processing shared task featured a track
focused on the de-identification of longitudinal medical records. For this track, we de …

[HTML][HTML] Automated systems for the de-identification of longitudinal clinical narratives: Overview of 2014 i2b2/UTHealth shared task Track 1

A Stubbs, C Kotfila, Ö Uzuner - Journal of biomedical informatics, 2015 - Elsevier
Abstract The 2014 i2b2/UTHealth Natural Language Processing (NLP) shared task featured
four tracks. The first of these was the de-identification track focused on identifying protected …

Use of unstructured text in prognostic clinical prediction models: a systematic review

TM Seinen, EA Fridgeirsson, S Ioannou… - Journal of the …, 2022 - academic.oup.com
Objective This systematic review aims to assess how information from unstructured text is
used to develop and validate clinical prognostic prediction models. We summarize the …