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 …

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 …

Annotation and initial evaluation of a large annotated German oncological corpus

M Kittner, M Lam**, DT Rieke, J Götze, B Bajwa… - JAMIA …, 2021 - academic.oup.com
Abstract Objective We present the Berlin-Tübingen-Oncology corpus (BRONCO), a large
and freely available corpus of shuffled sentences from German oncological discharge …

A distributable German clinical corpus containing cardiovascular clinical routine doctor's letters

P Richter-Pechanski, P Wiesenbach, DM Schwab… - Scientific Data, 2023 - nature.com
We present CARDIO: DE, the first freely available and distributable large German clinical
corpus from the cardiovascular domain. CARDIO: DE encompasses 500 clinical routine …

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 …

Extracting and structuring information from the electronic medical text: state of the art and trendy directions

MY Landolsi, L Hlaoua, LB Romdhane - Multimedia Tools and …, 2024 - Springer
In the medical field, doctors must have comprehensive knowledge by reading and writing
narrative documents, and they are responsible for every decision they take for patients …

Automatic extraction of 12 cardiovascular concepts from German discharge letters using pre-trained language models

P Richter-Pechanski, NA Geis, C Kiriakou… - Digital …, 2021 - journals.sagepub.com
Objective A vast amount of medical data is still stored in unstructured text documents. We
present an automated method of information extraction from German unstructured clinical …

Annotating German clinical documents for de-identification

T Kolditz, C Lohr, J Hellrich… - … 2019: Health and …, 2019 - ebooks.iospress.nl
We devised annotation guidelines for the de-identification of German clinical documents and
assembled a corpus of 1,106 discharge summaries and transfer letters with 44K annotated …

[HTML][HTML] Optimized identification of advanced chronic kidney disease and absence of kidney disease by combining different electronic health data resources and by …

C Weber, L Röschke, L Modersohn, C Lohr… - Journal of Clinical …, 2020 - mdpi.com
Automated identification of advanced chronic kidney disease (CKD≥ III) and of no known
kidney disease (NKD) can support both clinicians and researchers. We hypothesized that …

Clinical information extraction for lower-resource languages and domains with few-shot learning using pretrained language models and prompting

P Richter-Pechanski, P Wiesenbach… - Natural Language …, 2024 - cambridge.org
A vast amount of clinical data are still stored in unstructured text. Automatic extraction of
medical information from these data poses several challenges: high costs of clinical …