Dr. Alexander Oeser

Software Developer, Synagen GmbH Dresden

alexander.oeser@medizin.uni-leipzig.de

Background and Position

I’m an alumni of the Leipzig University of Applied Sciences since 2015 and finished my studies with a Master of Engineering (M.Eng.) degree in Engineering Economics. My academical focus was mainly on digital product development. In addition, I’ve been at ICCAS as a scientific assistant since 2011. In late 2016, I’ve joined the Digital Patient Model (DPM) research group to support the development of patient- and information models in head and neck oncology.

Since the beginning of 2020, I’m taking care of development tasks associated with the H2020 ERA-NET project “ProDial” as a senior scientist. Furthermore, I am involved in the AG Artificial Intelligence in Hematology for the development of AI-assisted solutions for clinical decision-support.

Research Areas

Patient- and Information Modeling
Knowledge Engineering and Knowledge Fusion
Artificial Intelligence and Machine Learning
Risk Assessment and Prediction
Medical Software Architecture and Development
Frontend and User Experience Development

Publications

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Oeser A, Grieb N, Gaebel J, Franke S, Kubasch AS, Merz M, et al. Künstliche Intelligenz in der Entscheidungsunterstützung und medikamentösen Tumortherapie. Onkologie [Internet]. 2024 [cited 2024 May 15];30(5):380–7. Available from: https://link.springer.com/10.1007/s00761-024-01487-1

Grieb N, Schmierer L, Kim HU, Strobel S, Schulz C, Meschke T, et al. A digital twin model for evidence-based clinical decision support in multiple myeloma treatment. Front Digit Health. 2023;5:1324453.

Grieb N, Oeser A, Kubasch AS, Wang SY, Lilienfeld-Toal M von, Yomade O, et al. P-212: Quantifying the average treatment effect of single vs. tandem autologous stem cell transplantation in newly diagnosed multiple myeloma using causal inference. In: Clinical Lymphoma, Myeloma and Leukemia [Internet]. Elsevier; 2022 [cited 2022 Dec 5]. p. S151–2. Available from: https://www.clinical-lymphoma-myeloma-leukemia.com/article/S2152-2650(22)00542-0/abstract

Buyer J, Oeser A, Grieb N, Dietz A, Neumuth T, Stoehr M. Decision Support for Oropharyngeal Cancer Patients Based on Data-Driven Similarity Metrics for Medical Case Comparison. Diagnostics (Basel). 2022 Apr 15;12(4):999.

Huehn M, Gaebel J, Oeser A, Dietz A, Neumuth T, Wichmann G, et al. Bayesian Networks to Support Decision-Making for Immune-Checkpoint Blockade in Recurrent/Metastatic (R/M) Head and Neck Squamous Cell Carcinoma (HNSCC). Cancers (Basel). 2021 Nov 23;13(23):5890.

Kubasch AS, Grieb N, Oeser A, Neumuth T, Yomade O, Hochhaus A, et al. Predicting Early Relapse for Patients with Multiple Myeloma through Machine Learning. In: Blood [Internet]. 2021 [cited 2022 Dec 5]. p. 2953. Available from: https://www.sciencedirect.com/science/article/pii/S0006497121048904

Kubasch AS, Oeser A, Grieb N, Meschke T, Weigert A, Gloaguen S, et al. Development of a semantic and causal model for treatment decision making in myelodysplastic syndromes. In: Jahrestagung der Dt Gesellschaft für Hämatologie und Medizinische Onkologie (DGHO). 2021.

Nenoff K, Grieb N, Oeser A, Neumuth T, Platzbecker U, Kubasch AS. [Künstliche Intelligenz in der Hämatologie]. InFo Hämatologie und Onkologie. 2021;24(12):10–2.

Müller J, Stoehr M, Oeser A, Gaebel J, Streit M, Dietz A, et al. A visual approach to explainable computerized clinical decision support. Computers & Graphics [Internet]. 2020 Oct 1 [cited 2020 Jul 14];91:1–11. Available from: http://www.sciencedirect.com/science/article/pii/S0097849320300935

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Gaebel J, Wu HG, Oeser A, Cypko MA, Stoehr M, Dietz A, et al. Modeling and Processing Up-To-Dateness of Patient Information in Probabilistic Therapy Decision Support. Artif Intell Med 2020 [Internet]. 2020 [cited 2020 Mar 12];101842. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0933365719302945

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Oeser A, Gaebel J, Kuhnt T. Development of an Assistance System for the Intuitive Assessment of Laboratory Findings in Oncology. Current Directions in Biomedical Engineering [Internet]. 2019 [cited 2019 Oct 2];5(1):61–4. Available from: https://www.degruyter.com/view/j/cdbme.2019.5.issue-1/cdbme-2019-0016/cdbme-2019-0016.xml?format=INT

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Gaebel J, Oeser A, Dietz A, Oeltze-Jafra S. Bayesian Networks for Oncological Therapy Decision Support. In Edinburgh; 2018.

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Gaebel J, Wu HG, Oeser A, Oeltze-Jafra S. System Infrastructure for Probabilistic Decision Models in Cancer Treatment. In: Building Continents of Knowledge in Oceans of Data: the Future of Co-Created eHealth. Göteborg; 2018.

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Oeser A, Gaebel J, Dietz A, Wiegand S, Oeltze-Jafra S. Information architecture for a patient-specific dashboard in head and neck tumor boards. Int J Comput Assist Radiol Surg. 2018 Mar 28;

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Gaebel J, Oeser A, Müller J, Schreiber E, Oeltze-Jafra S. Probabilistic Patient Modeling for Therapeutic Decision Support in Oncology. 23rd ISfTeH International Conference on Telemedicine and eHealth; 2018 Mar 24; Helsinki.

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Oeser A, Gaebel J, Müller J, Franke S. Design Concept of an Information System for the Intuitive Assessment of Laboratory Findings. In: Proceedings of the 2017 Workshop on Visual Analytics in Healthcare (VAHC 2018). San Francisco, CA; 2018.

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Gaebel J, Schreiber E, Oeser A, Oeltze-Jafra S. Modular Architecture for Integrated Model-Based Decision Support. Stud Health Technol Inform. 2018;248:108–15.

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Gaebel J, Wu HG, Oeser A, Schreiber E, Oeltze-Jafra S. Modular Architecture for Integrated Model-Based Decision Support. In: 12th Annual Conference on Health Informatics meets eHealth. 2018. p. accepted.

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Maktabi M, Birnbaum K, Oeser A, Neumuth T. Situation-dependent medical device risk estimation: Design and Evaluation of an equipment management center for vendor-independent integrated operating rooms. J Patient Saf. 2017;in print.

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Oeser A. Conceptual development of a remote cockpit for the use in telesurgery. 2015.