Sie befinden sich hier
- Experimental stroke research on mouse models
- Operative methods of ischemic mouse models (filament occlusion) and SAB models (filament perforation); (see list of publications No. 2)
- Micro-CT, DSA (see publication list no. 2).
Biostatistics/computer science (MSc)
- Machine learning on genetic, image and text data
(see publication list no. 1, 3 & 5)
- Prognostic and predictive outcome modeling
(see publication list no. 4, 6 & 7)
Dr. Maros is a senior radiology resident just before his board certification exam at the Department of Neuroradiology. He is also involved in the MIRACUM Consortium Project in the framework of the BMWI Medical Informatics Initiative and affiliated with the Department of Biomedical Informatics, Medical Faculty Mannheim (Prof. Dr. T. Ganslandt). He is the co-founder and machine learning specialist of our research group (Applied Medical Image & Data Analysis; AMIDL; neurorad.xyz). He is interested in tackling everyday challenges that radiologists face using the power of underlying patterns and math thus improving the quality of care benefitting our patients and community.
We developed a customizable light-weight, open-source data extraction and preprocessing pipeline (dubbed “Radiology Information and PACS Extractor: RIPE”; left) that enables automated bulk information retrieval tailored for consequent modular deployment of downstream prognostic and predictive models (right).
Source: neurorad.xyz (M.Maros).
Real-time decision support for cerebral vasospasm detection on conventional angiograms using deep learning;
Source: neurorad.xyz (M.Maros).
Micro-CT of a sham operated mouse (a) without SAH and of a mouse with SAH (b) after filament perforation.
Source: the image is a modified version of Fig. 3 in Weyer V*, Maros ME* et al. Longitudinal imaging and evaluation of sah-associated cerebral large artery vasospasm in mice using micro-ct and angiography. J Cereb Blood Flow Metab. 2019:271678X19887052; <link to publication>.
National and international joint research projects
Participation in the MIRACUM Consortium funded by the German Ministry for Education and Research (BMBF) within the framework of the Medical Informatics Initiative, which was launched in 2015.
- Maros ME, Capper D, Jones DTW, Hovestadt V, von Deimling A, Pfister SM, et al. Machine learning workflows to estimate class probabilities for precision cancer diagnostics on DNA methylation microarray data. Nat Protoc. 2020;15:479-512
- Weyer V*, Maros ME*, Kronfeld A, Kirschner S, Groden C, Sommer C, et al. Longitudinal imaging and evaluation of sah-associated cerebral large artery vasospasm in mice using micro-ct and angiography. J Cereb Blood Flow Metab. 2019:271678X19887052
- Maros ME, Schnaidt S, Balla P, Kelemen Z, Sapi Z, Szendroi M, et al. In situ cell cycle analysis in giant cell tumor of bone reveals patients with elevated risk of reduced progression-free survival. Bone. 2019;127:188-198
- Forster A, Bohme J, Maros ME, Brehmer S, Seiz-Rosenhagen M, Hanggi D, et al. Longitudinal mri findings in patients with newly diagnosed glioblastoma after intraoperative radiotherapy. J Neuroradiol. 2019
- Maros ME, Wenz R, Forster A, Froelich MF, Groden C, Sommer WH, et al. Objective comparison using guideline-based query of conventional radiological reports and structured reports. In Vivo. 2018;32:843-849
- Forster A, Wenz R, Maros ME, Bohme J, Al-Zghloul M, Alonso A, et al. Anatomical distribution of cerebral microbleeds and intracerebral hemorrhage in vertebrobasilar dolichoectasia. PLoS One. 2018;13:e0196149
- Wenz H, Wenz R, Maros M, Ehrlich G, Al-Zghloul M, Groden C, et al. Incidence, locations, and longitudinal course of cerebral microbleeds in european moyamoya. Stroke. 2017;48:307-313
Photo Credits: #1 FGV-Zentrum, Med. Fakultät Mannheim
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