Neural natural language processing for unstructured data in electronic health records: a review

I Li, J Pan, J Goldwasser, N Verma, WP Wong… - Computer Science …, 2022 - Elsevier
Electronic health records (EHRs), digital collections of patient healthcare events and
observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and …

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 …

[图书][B] Healthcare data analytics

CK Reddy, CC Aggarwal - 2015 - books.google.com
Supplying a comprehensive overview of healthcare analytics research, Healthcare Data
Analytics provides an understanding of the analytical techniques currently available to solve …

Current approaches to identify sections within clinical narratives from electronic health records: a systematic review

A Pomares-Quimbaya, M Kreuzthaler… - BMC medical research …, 2019 - Springer
Background The identification of sections in narrative content of Electronic Health Records
(EHR) has demonstrated to improve the performance of clinical extraction tasks; however …

Task 2: ShARe/CLEF eHealth evaluation lab 2014

DL Mowery, S Velupillai, BR South… - Proceedings of CLEF …, 2014 - hal.science
This paper reports on Task 2 of the 2014 ShARe/CLEF eHealth evaluation lab which
extended Task 1 of the 2013 ShARe/CLEF eHealth evaluation lab by focusing on template …

Hybrid method to automatically extract medical document tree structure

MY Landolsi, L Hlaoua, LB Romdhane - Engineering Applications of …, 2023 - Elsevier
A huge and rapidly growing quantity of medical documents is available in an electronic
versions. These informing documents mostly have textual content in natural language …

Automatic classification of mammography reports by BI-RADS breast tissue composition class

B Percha, H Nassif, J Lipson… - Journal of the …, 2012 - academic.oup.com
Because breast tissue composition partially predicts breast cancer risk, classification of
mammography reports by breast tissue composition is important from both a scientific and …

BI-RADS BERT and using section segmentation to understand radiology reports

G Kuling, B Curpen, AL Martel - Journal of Imaging, 2022 - mdpi.com
Radiology reports are one of the main forms of communication between radiologists and
other clinicians, and contain important information for patient care. In order to use this …

Leveraging medical literature for section prediction in electronic health records

S Rosenthal, K Barker, Z Liang - Proceedings of the 2019 …, 2019 - aclanthology.org
Abstract Electronic Health Records (EHRs) contain both structured content and unstructured
(text) content about a patient's medical history. In the unstructured text parts, there are …

[HTML][HTML] Building an automated SOAP classifier for emergency department reports

D Mowery, J Wiebe, S Visweswaran, H Harkema… - Journal of biomedical …, 2012 - Elsevier
Information extraction applications that extract structured event and entity information from
unstructured text can leverage knowledge of clinical report structure to improve …