Philipp Daumke
Overview
Explore the profile of Philipp Daumke including associated specialties, affiliations and a list of published articles.
Author names and details appear as published. Due to indexing inconsistencies, multiple individuals may share a name, and a single author may have variations. MedLuna displays this data as publicly available, without modification or verification
Snapshot
Snapshot
Articles
22
Citations
173
Followers
0
Related Specialties
Related Specialties
Top 10 Co-Authors
Top 10 Co-Authors
Published In
Published In
Affiliations
Affiliations
Soon will be listed here.
Recent Articles
1.
Legnar M, Daumke P, Hesser J, Porubsky S, Popovic Z, Bindzus J, et al.
Diagnostics (Basel)
. 2022 Jul;
12(7).
PMID: 35885630
Introduction: This study investigates whether it is possible to predict a final diagnosis based on a written nephropathological description-as a surrogate for image analysis-using various NLP methods. Methods: For this...
2.
Caliskan D, Zierk J, Kraska D, Schulz S, Daumke P, Prokosch H, et al.
Stud Health Technol Inform
. 2021 May;
278:224-230.
PMID: 34042898
Introduction: The aim of this study is to evaluate the use of a natural language processing (NLP) software to extract medication statements from unstructured medical discharge letters. Methods: Ten randomly...
3.
Grundel B, Bernardeau M, Langner H, Schmidt C, Bohringer D, Ritter M, et al.
Ophthalmologe
. 2020 Jul;
118(3):264-272.
PMID: 32725541
Background: Anti-VEGF drugs are currently used to treat macular diseases. This has led to a wealth of additional data, which could help understand and predict treatment courses; however, this information...
4.
Pokora R, Le Cornet L, Daumke P, Mildenberger P, Zeeb H, Blettner M
Gesundheitswesen
. 2020 Jan;
82(S 02):S165.
PMID: 31962360
No abstract available.
5.
Pokora R, Le Cornet L, Daumke P, Mildenberger P, Zeeb H, Blettner M
Gesundheitswesen
. 2019 Oct;
82(S 02):S158-S164.
PMID: 31597185
Hintergrund: In Sekundärdaten existieren oftmals unstrukturierte Freitexte. In dieser Arbeit wird ein Text-Mining-System validiert, um unstrukturierte medizinische Daten für Forschungszwecke zu extrahieren. Methoden: Aus einer radiologischen Klinik wurden aus 7102...
6.
Daumke P, Heitmann K, Heckmann S, Martinez-Costa C, Schulz S
Stud Health Technol Inform
. 2019 Aug;
264:83-87.
PMID: 31437890
Semantic standards and human language technologies are key enablers for semantic interoperability across heterogeneous document and data collections in clinical information systems. Data provenance is awarded increasing attention, and it...
7.
Winter A, Staubert S, Ammon D, Aiche S, Beyan O, Bischoff V, et al.
Methods Inf Med
. 2018 Jul;
57(S 01):e92-e105.
PMID: 30016815
Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. "Smart Medical Information Technology for Healthcare (SMITH)" is one...
8.
Prokosch H, Acker T, Bernarding J, Binder H, Boeker M, Boerries M, et al.
Methods Inf Med
. 2018 Jul;
57(S 01):e82-e91.
PMID: 30016814
Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. Similar to other large international data sharing networks (e.g....
9.
Lopez-Garcia P, Kreuzthaler M, Schulz S, Scherr D, Daumke P, Marko K, et al.
Stud Health Technol Inform
. 2016 May;
223:93-9.
PMID: 27139390
The vast amount of clinical data in electronic health records constitutes a great potential for secondary use. However, most of this content consists of unstructured or semi-structured texts, which is...
10.
Kreuzthaler M, Daumke P, Schulz S
Stud Health Technol Inform
. 2015 Jun;
212:9-14.
PMID: 26063251
Patients with chronic diseases undergo numerous in- and outpatient treatment periods, and therefore many documents accumulate in their electronic records. We report on an on-going project focussing on the semantic...