Publications

1005 Publications visible to you, out of a total of 1005

Abstract (Expand)

We present a working approach for a clinical research database as part of an archival information system. The CDISC ODM standard is target for clinical study and research relevant routine data, thus decoupling the data ingest process from the access layer. The presented research database is comprehensive as it covers annotating, mapping and curation of poorly annotated source data. Besides a conventional relational database the medical data warehouse i2b2 serves as main frontend for end-users. The system we developed is suitable to support patient recruitment, cohort identification and quality assurance in daily routine.

Authors: Frank Meineke, Sebastian Stäubert, Matthias Löbe, Alfred Winter

Date Published: 2014

Publication Type: Journal article

Abstract

Not specified

Authors: Franziska Jahn, M. Schaaf, Barbara Paech, Alfred Winter

Date Published: 2014

Publication Type: InCollection

Abstract

Not specified

Authors: Elske Ammenwerth, Reinhold Haux, Petra Knaup-Gregori, Alfred Winter

Date Published: 2014

Publication Type: Book

Abstract

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Authors: Lutz J Heinrich, René Riedl, Dirk Stelzer

Date Published: 2014

Publication Type: Book

Abstract

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Authors: Franziska Jahn, Michael Schaaf, Barbara Paech, Alfred Winter

Date Published: 2014

Publication Type: InProceedings

Abstract (Expand)

As revealed by optical coherence tomography (OCT), the shape of the fovea may vary greatly among individuals. However, none of the hitherto available mathematical descriptions comprehensively reproduces all individual characteristics such as foveal depth, slope, naso-temporal asymmetry, and others. Here, a novel mathematical approach is presented to obtain a very accurate model of the complete 3D foveal surface of an individual, by utilizing recent developments in OCT. For this purpose, a new formula was developed serving as a simple but very flexible way to represent a given fovea. An extensive description of the used model parameters, as well as, of the complete method of reconstructing a foveal surface from OCT data, is presented. Noteworthy, the formula analytically provides characteristic foveal parameters and thus allows for extensive quantification. The present approach was verified on 432 OCT scans and has proved to be able to capture the whole range of asymmetric foveal shapes with high accuracy (i.e. a mean fit error of 1.40 mum).

Authors: P. Scheibe, A. Lazareva, U. D. Braumann, A. Reichenbach, P. Wiedemann, M. Francke, F. G. Rauscher

Date Published: 3rd Dec 2013

Publication Type: Not specified

Human Diseases: eye disease

Abstract (Expand)

We present an analytic framework based on Self-Organizing Map (SOM) machine learning to study large scale patient data sets. The potency of the approach is demonstrated in a case study using gene expression data of more than 200 mature aggressive B-cell lymphoma patients. The method portrays each sample with individual resolution, characterizes the subtypes, disentangles the expression patterns into distinct modules, extracts their functional context using enrichment techniques and enables investigation of the similarity relations between the samples. The method also allows to detect and to correct outliers caused by contaminations. Based on our analysis, we propose a refined classification of B-cell Lymphoma into four molecular subtypes which are characterized by differential functional and clinical characteristics.

Authors: L. Hopp, K. Lembcke, H. Binder, H. Wirth

Date Published: 2nd Dec 2013

Publication Type: Not specified

Human Diseases: non-Hodgkin lymphoma, B-cell lymphoma

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