Miriam Elia M.Sc.
Phone: | +49 821 598 2472 |
Email: | miriam.elia@informatik.uni-augsburginformatik.uni-augsburg.de () |
Room: | 3004 (N) |
Address: | Universitätsstraße 6a, 86159 Augsburg |
Short Resume
- Since December 2021: PhD candidate, Chair of Software Methodologies for Distributed Systems, University of Augsburg
- 2021: Master’s degree in Business & Information Systems Engineering, University of Augsburg
- 2019: Bachelor’s degree in Business & Information Systems Engineering, University of Augsburg
- 2016: Bachelor of Education in English & French, University of Augsburg
Research Area
- Trustworthy AI
- Machine Learning in Healthcare
- Certifiable AI in Medicine
- Creation of a Generic and Customizable Methodology based on Quality Gates towards Certifiable AI in Medicine
Projects
Mentored Theses
- "Zusammenführung multimodaler Datenquellen in einer Anwendung zur Analyse des Ösophagus für die Diagnoseunterstützung von Achalasie" - Master Thesis
Publications
2024 |
Vivian Grünherz, Alanna Ebigbo, Miriam Elia, Alessandra Brunner, Tamara Krafft, Leo Pöller, Pia Schneider, Fabian Stieler, Bernhard Bauer, Anna Muzalyova, Helmut Messmann and Sandra Nagl. 2024. Automatic three-dimensional reconstruction of the oesophagus in achalasia patients undergoing POEM: an innovative approach for evaluating treatment outcomes. BMJ Open Gastroenterology 11, 1, e001396. DOI: 10.1136/bmjgast-2024-001396 |
Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle, Robin Schön, Katja Ludwig, Rainer Lienhart, Simon Jegou, Guang Li, Cong Chen, Qi Wang, Derik Shi, Mayug Maniparambil, Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Ine Dirks, Matias Nicolas Bossa, Abel Diaz Berenguer, Tanmoy Mukherjee, Jef Vandemeulebroucke, Hichem Sahli, Nikos Deligiannis, Panagiotis Gonidakis, Ngoc Dung Huynh, Imran Razzak, Reda Bouadjenek, Mario Verdicchio, Pasquale Borrelli, Marco Aiello, James A. Meakin, Alexander Lemm, Christoph Russ, Razvan Ionasec, Nikos Paragios, Bram van Ginneken and Marie-Pierre Revel Dubios. 2024. The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data. Medical Image Analysis 97, 103230. DOI: 10.1016/j.media.2024.103230 |
2023 |
Miriam Elia and Bernhard Bauer. 2023. A methodology based on quality gates for certifiable AI in medicine: towards a reliable application of metrics in machine learning. In Hans-Georg Fill, Francisco José Domínguez Mayo, Marten van Sinderen, Leszek Maciaszek (Eds.). ICSOFT 2023: Proceedings of the 18th International Conference on Software Technologies, 10-12 July 2023, Rome, Italy. SciTePress, Setúbal, 486-493 DOI: 10.5220/0012121300003538 |
Fabian Stieler, Miriam Elia, Benjamin Weigell, Bernhard Bauer, Peter Kienle, Anton Roth, Gregor Müllegger, Marius Nann and Sarah Dopfer. 2023. LIFEDATA - a framework for traceable active learning projects. In Kurt Schneider, Fabiano Dalpiaz, Jennifer Horkoff (Eds.). 2023 IEEE 31st International Requirements Engineering Conference Workshops (REW), 4-5 September 2023, Hannover, Germany. IEEE, Piscataway, NJ, 465-474 DOI: 10.1109/REW57809.2023.00088 |
Miriam Elia, Tobias Peter, Fabian Stieler, Bernhard Bauer, Sandra Nagl, Alanna Ebigbo and Vivien Grünherz. in press. Precision medicine for achalasia diagnosis: a multi-modal and interdisciplinary approach for training data generation [Abstract]. In IEEE - ISBI 2023: International Symposium on Biomedical Imaging, Cartagena de Indias, Colombia, April 18-21, 2023. IEEE, Piscataway, NJ |
Dominik Mueller, Silvan Mertes, Niklas Schroeter, Fabio Hellmann, Miriam Elia, Bernhard Bauer, Wolfgang Reif, Elisabeth André and Frank Kramer. 2023. Towards automated COVID-19 presence and severity classification. In Maria Hägglund, Madeleine Blusi, Stefano Bonacina, Lina Nilsson, Inge Cort Madsen, Sylvia Pelayo, Anne Moen, Arriel Benis, Lars Lindsköld and Parisis Gallos (Ed.). Caring is sharing – exploiting the value in data for health and innovation. IOS Press, Amsterdam (Studies in Health Technology and Informatics ; 302), 917-921. DOI: 10.3233/shti230309 |
2021 |
Miriam Elia, Carola Gajek, Alexander Schiendorfer and Wolfgang Reif. 2021. An interactive web application for decision tree learning. In Bernd Bischl, Oliver Guhr, Heidi Seibold and Peter Steinbach (Ed.). Proceedings of the Teaching Machine Learning Workshop at ECML-PKDD 2020, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 14 September 2020, Virtual Conference. ML Research Press (PMLR - Proceedings of Machine Learning Research ; 141), 11-16. |