@inproceedings{BehbahaniRibleMoulinecetal.2015,
  author    = {Behbahani, Mehdi and Rible, Sebastian and Moulinec, Charles and Fournier, Yvan and Nicolai, Mike and Crosetto, Paolo},
  title     = {Simulation of the FDA Centrifugal Blood Pump Using High Performance Computing},
  series = {World Academy of Science, Engineering and Technology International Journal of Mechanical and Mechatronics Engineering},
  volume    = {9},
  booktitle = {World Academy of Science, Engineering and Technology International Journal of Mechanical and Mechatronics Engineering},
  number    = {5},
  year      = {2015},
  language  = {en}
}
@inproceedings{MarinovaKerroumiLintermannetal.2016,
  author    = {Marinova, V. and Kerroumi, I. and Lintermann, A. and G{\"o}bbert, J.H. and Moulinec, C. and Rible, S. and Fournier, Y. and Behbahani, Mehdi},
  title     = {Numerical Analysis of the FDA Centrifugal Blood Pump},
  series = {NIC Symposium 2016},
  booktitle = {NIC Symposium 2016},
  isbn      = {978-3-95806-109-5},
  pages     = {355 -- 364},
  year      = {2016},
  language  = {de}
}
@inproceedings{SchmidtsKraftSiebigterothetal.2019,
  author    = {Schmidts, Oliver and Kraft, Bodo and Siebigteroth, Ines and Z{\"u}ndorf, Albert},
  title     = {Schema Matching with Frequent Changes on Semi-Structured Input Files: A Machine Learning Approach on Biological Product Data},
  series = {Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS},
  booktitle = {Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 1: ICEIS},
  isbn      = {978-989-758-372-8},
  doi       = {10.5220/0007723602080215},
  pages     = {208 -- 215},
  year      = {2019},
  language  = {en}
}
@inproceedings{HunkerJungGossmannetal.2019,
  author    = {Hunker, Jan and Jung, Alexander and Goßmann, Matthias and Linder, Peter and Staat, Manfred},
  title     = {Development of a tool to analyze the conduction speed in microelectrode array measurements of cardiac tissue},
  series = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen},
  booktitle = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen},
  editor    = {Staat, Manfred and Erni, Daniel},
  publisher = {Universit{\"a}t Duisburg-Essen},
  address   = {Duisburg},
  organization    = {MedTech Symposium},
  isbn      = {978-3-940402-22-6},
  doi       = {10.17185/duepublico/48750},
  pages     = {7 -- 8},
  year      = {2019},
  abstract  = {The discovery of human induced pluripotent stem cells reprogrammed from somatic cells [1] and their ability to differentiate into cardiomyocytes (hiPSC-CMs) has provided a robust platform for drug screening [2]. Drug screenings are essential in the development of new components, particularly for evaluating the potential of drugs to induce life-threatening pro-arrhythmias. Between 1988 and 2009, 14 drugs have been removed from the market for this reason [3]. The microelectrode array (MEA) technique is a robust tool for drug screening as it detects the field potentials (FPs) for the entire cell culture. Furthermore, the propagation of the field potential can be examined on an electrode basis. To analyze MEA measurements in detail, we have developed an open-source tool.},
  language  = {en}
}
@inproceedings{RamanJungHorvathetal.2019,
  author    = {Raman, Aravind Hariharan and Jung, Alexander and Horv{\´a}th, Andr{\´a}s and Becker, Nadine and Staat, Manfred},
  title     = {Modification of a computer model of human stem cell-derived cardiomyocyte electrophysiology based on Patch-Clamp measurements},
  series = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen},
  booktitle = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen},
  editor    = {Staat, Manfred and Erni, Daniel},
  publisher = {Universit{\"a}t Duisburg-Essen},
  address   = {Duisburg},
  organization    = {MedTech Symposium},
  isbn      = {978-3-940402-22-6},
  doi       = {10.17185/duepublico/48750},
  pages     = {10 -- 11},
  year      = {2019},
  abstract  = {Human induced pluripotent stem cells (hiPSCs) have shown to be promising in disease studies and drug screenings [1]. Cardiomyocytes derived from hiPSCs have been extensively investigated using patch-clamping and optical methods to compare their electromechanical behaviour relative to fully matured adult cells. Mathematical models can be used for translating findings on hiPSCCMs to adult cells [2] or to better understand the mechanisms of various ion channels when a drug is applied [3,4]. Paci et al. (2013) [3] developed the first model of hiPSC-CMs, which they later refined based on new data [3]. The model is based on iCells® (Fujifilm Cellular Dynamics, Inc. (FCDI), Madison WI, USA) but major differences among several cell lines and even within a single cell line have been found and motivate an approach for creating sample-specific models. We have developed an optimisation algorithm that parameterises the conductances (in S/F=Siemens/Farad) of the latest Paci et al. model (2018) [5] using current-voltage data obtained in individual patch-clamp experiments derived from an automated patch clamp system (Patchliner, Nanion Technologies GmbH, Munich).},
  language  = {en}
}
@inproceedings{AzarDigel2019,
  author    = {Azar, Fouad and Digel, Ilya},
  title     = {Utilization of fluorescence spectroscopy and neural networks in clinical analysis},
  series = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen},
  booktitle = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen},
  editor    = {Staat, Manfred and Erni, Daniel},
  publisher = {Universit{\"a}t Duisburg-Essen},
  address   = {Duisburg},
  organization    = {MedTech Symposium},
  isbn      = {978-3-940402-22-6},
  doi       = {10.17185/duepublico/48750},
  pages     = {40 -- 41},
  year      = {2019},
  abstract  = {Fluorescence topography of human urine in combination with learning algorithms can provide a variant pattern recognition method in analytical clinical chemistry and, eventually, diagnosis.},
  language  = {en}
}
@inproceedings{ZingsheimGrimmerOrtneretal.2019,
  author    = {Zingsheim, Jonas and Grimmer, Timo and Ortner, Marion and Schmaderer, Christoph and Hauser, Christine and Kotliar, Konstantin},
  title     = {Recognition of subjects with mild cognitive impairment (MCI) by the use of retinal arterial vessels.},
  series = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen},
  booktitle = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen},
  editor    = {Staat, Manfred and Erni, Daniel},
  publisher = {Universit{\"a}t Duisburg-Essen},
  address   = {Duisburg},
  organization    = {MedTech Symposium},
  isbn      = {978-3-940402-22-6},
  doi       = {10.17185/duepublico/48750},
  pages     = {36 -- 37},
  year      = {2019},
  language  = {en}
}
@inproceedings{BlumAlbannaBenninghausetal.2019,
  author    = {Blum, Yannik and Albanna, Walid and Benninghaus, Anne and Kotliar, Konstantin},
  title     = {Vasomotion in retinal vessels of patients presenting post hemorrhagic hydrocephalus following subarachnoid hemorrhage},
  series = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen},
  booktitle = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH Aachen},
  editor    = {Staat, Manfred and Erni, Daniel},
  publisher = {Universit{\"a}t Duisburg-Essen},
  address   = {Duisburg},
  organization    = {MedTech Symposium},
  isbn      = {978-3-940402-22-6},
  doi       = {10.17185/duepublico/48750},
  pages     = {38 -- 39},
  year      = {2019},
  abstract  = {Clearance of blood components and fluid drainage play a crucial role in subarachnoid hemorrhage (SAH) and post hemorrhagic hydrocephalus (PHH). With the involvement of interstitial fluid (ISF) and cerebrospinal fluid (CSF), two pathways for the clearance of fluid and solutes in the brain are proposed. Starting at the level of capillaries, flow of ISF follows along the basement membranes in the walls of cerebral arteries out of the parenchyma to drain into the lymphatics and CSF [1]-[3]. Conversely, it is shown that CSF enters the parenchyma between glial and pial basement membranes of penetrating arteries [4]-[6]. Nevertheless, the involved structures and the contribution of either flow pathway to fluid balance between the subarachnoid space and interstitial space remains controversial. Low frequency oscillations in vascular tone are referred to as vasomotion and corresponding vasomotion waves are modeled as the driving force for flow of ISF out of the parenchyma [7]. Retinal vessel analysis (RVA) allows non-invasive measurement of retinal vessel vasomotion with respect to diameter changes [8]. Thus, the aim of the study is to investigate vasomotion in RVA signals of SAH and PHH patients.},
  language  = {en}
}
@inproceedings{SiebigterothKraftSchmidtsetal.2019,
  author    = {Siebigteroth, Ines and Kraft, Bodo and Schmidts, Oliver and Z{\"u}ndorf, Albert},
  title     = {A Study on Improving Corpus Creation by Pair Annotation},
  series = {Proceedings of the Poster Session of the 2nd Conference on Language, Data and Knowledge (LDK-PS 2019)},
  booktitle = {Proceedings of the Poster Session of the 2nd Conference on Language, Data and Knowledge (LDK-PS 2019)},
  issn      = {1613-0073},
  pages     = {40 -- 44},
  year      = {2019},
  language  = {en}
}
@inproceedings{KromeSander2018,
  author    = {Krome, Cornelia and Sander, Volker},
  title     = {Time series analysis with apache spark and its applications to energy informatics},
  series = {Proceedings of the 7th DACH+ Conference on Energy Informatics},
  booktitle = {Proceedings of the 7th DACH+ Conference on Energy Informatics},
  doi       = {10.1186/s42162-018-0043-1},
  year      = {2018},
  abstract  = {In energy economy forecasts of different time series are rudimentary. In this study, a prediction for the German day-ahead spot market is created with Apache Spark and R. It is just an example for many different applications in virtual power plant environments. Other examples of use as intraday price processes, load processes of machines or electric vehicles, real time energy loads of photovoltaic systems and many more time series need to be analysed and predicted. This work gives a short introduction into the project where this study is settled. It describes the time series methods that are used in energy industry for forecasts shortly. As programming technique Apache Spark, which is a strong cluster computing technology, is utilised. Today, single time series can be predicted. The focus of this work is on developing a method to parallel forecasting, to process multiple time series simultaneously with R and Apache Spark.},
  language  = {en}
}