[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 …

[HTML][HTML] Natural language processing of clinical notes on chronic diseases: systematic review

S Sheikhalishahi, R Miotto, JT Dudley… - JMIR medical …, 2019 - medinform.jmir.org
Background: Novel approaches that complement and go beyond evidence-based medicine
are required in the domain of chronic diseases, given the growing incidence of such …

Model-assisted cohort selection with bias analysis for generating large-scale cohorts from the EHR for oncology research

B Birnbaum, N Nussbaum, K Seidl-Rathkopf… - arXiv preprint arXiv …, 2020 - arxiv.org
Objective Electronic health records (EHRs) are a promising source of data for health
outcomes research in oncology. A challenge in using EHR data is that selecting cohorts of …

Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives

S Gehrmann, F Dernoncourt, Y Li, ET Carlson, JT Wu… - PloS one, 2018 - journals.plos.org
In secondary analysis of electronic health records, a crucial task consists in correctly
identifying the patient cohort under investigation. In many cases, the most valuable and …

Natural language processing in oncology: a review

W Yim, M Yetisgen, WP Harris, SW Kwan - JAMA oncology, 2016 - jamanetwork.com
Importance Natural language processing (NLP) has the potential to accelerate translation of
cancer treatments from the laboratory to the clinic and will be a powerful tool in the era of …

Development of phenotype algorithms using electronic medical records and incorporating natural language processing

KP Liao, T Cai, GK Savova, SN Murphy, EW Karlson… - bmj, 2015 - bmj.com
Electronic medical records are emerging as a major source of data for clinical and
translational research studies, although phenotypes of interest need to be accurately …

[HTML][HTML] Clinical data reuse or secondary use: current status and potential future progress

SM Meystre, C Lovis, T Bürkle… - Yearbook of medical …, 2017 - thieme-connect.com
Objective: To perform a review of recent research in clinical data reuse or secondary use,
and envision future advances in this field. Methods: The review is based on a large literature …

Machine learning techniques for biomedical natural language processing: a comprehensive review

EH Houssein, RE Mohamed, AA Ali - IEEE Access, 2021 - ieeexplore.ieee.org
The widespread use of electronic health records (EHR) systems in health care provides a
large amount of real-world data, leading to new areas for clinical research. Natural language …

Natural language processing technologies in radiology research and clinical applications

T Cai, AA Giannopoulos, S Yu, T Kelil, B Ripley… - Radiographics, 2016 - pubs.rsna.org
The migration of imaging reports to electronic medical record systems holds great potential
in terms of advancing radiology research and practice by leveraging the large volume of …

Natural language–based machine learning models for the annotation of clinical radiology reports

J Zech, M Pain, J Titano, M Badgeley, J Schefflein… - Radiology, 2018 - pubs.rsna.org
Purpose To compare different methods for generating features from radiology reports and to
develop a method to automatically identify findings in these reports. Materials and Methods …