Prof. Dr. Murat Sariyar

Research and Teaching

Artificial intelligence in Medicine, Biostatistics, Bioinformatics, NLP, and Machine Learning

Data protection, Anonymization, and Record Linkage

Biomedical Ontologies and Data Management

Philosophy of Identity, Death and Events

Medical informatics (BSc)

Computer science (BSc)

Artificial Intelligence in Medicine (Master University Bern)

Databases and Advances Databases

Patient pathways and clinical processes

Business Intelligence in Healthcare

R as a programming language

Practical Machine Learning

Introduction to Bioinformatics and Genetic Epidemiology

Philosophy in the context of computer science

Mathematics for Data Science

Deep Learning

NLP and Text Mining

Computer Science & Medical Informatics & Bioinformatics

Mathematical Optimization

Machine Learning

Biostatistics and Bioinformatics

Pharmacogenetics CDSS

System Theory according to Luhmann

Data Protection and Anonymization

Record Linkage and Data Fusion

Ontology and Epistemology

Philosophy of Death and Identity

Harnessing event and longitudinal data in industry and the health sector through privacy preserving technologies (SNF)

Pharmacogenetic Clinical Decision Support Service (GebertRüf and InnoSuisse)

Record Linkage for Register-based Census (Destatis)

Innovative AI-supported documentation for emergency medicine (Inventus)

Citizen-controlled Data Science for Multiple Sclerosis Research (ETH)

Participatory roster planning based on trustworthy artificial intelligence (Intern)

https://scholar.google.ca/citations?user=VxIUUeQAAAAJ&hl

Sariyar, M., Tippenhauer, K., Philips, M., & Largiadèr, C. (2024). Using the PharmCAT tool for Pharmacogenetic clinical decision support. In Briefings in Bioinformatics (Vol. 25, Issue 1). Oxford University Press. https://doi.org/10.24451/arbor.20865

Sariyar, M., Aeschbacher, D. J., & Meissner, J. (2023). Nurse Scheduling with State-of-the Art Open-Source Tools. In J. Mantas, P. Gallos, E. Zoulias, A. Hasman, M. S. Hauseh, M. Charalampidou, & A. Magdalinou (Eds.), Studies in Health Technology and Informatics (Vol. 305). IOS Press. https://doi.org/10.24451/arbor.20872

Sariyar, M., & Miletic, M. (2023). What Kind of Ontologies Do We Need in the Biomedical Domain? In J. Mantas, P. Gallos, E. Zoulias, A. Hasman, M. S. Househ, M. Charalampidou, & A. Magdlinou (Eds.), Studies in Health Technology and Informatics (Vol. 305). IOS Press. https://doi.org/10.24451/arbor.20874

Miletic, M., & Sariyar, M. (2023). Implementing Informative-Based Active Learning in Biomedical Record Linkage for the Splink Package in Python. In J. Mantas, P. Gallos, E. Zoulias, A. Hasman, M. S. Househ, M. Charalampidou, & A. Magdalinou (Eds.), Studies in Health Technology and Informatics (Vol. 305). IOS Press. https://doi.org/10.24451/arbor.20913

Sariyar, M. (2023). Is Medical Informatics a Scientific Discipline or Just Applied Computer Science? In J. Mantas, P. Gallos, E. Zoulias, A. Hasman, M. S. Househ, M. Charalampidou, & A. Magdalinou (Eds.), Studies in Health Technology and Informatics (Vol. 305). IOS Press. https://doi.org/10.24451/arbor.20914

Wermelinger, J., Parduzi, Q., Sariyar, M., Raabe, A., Schneider, U. C., & Seidel, K. (2023). Opportunities and challenges of supervised machine learning for the classification of motor evoked potentials according to muscles. In BMC Medical Informatics and Decision Making (Vol. 23, Issue 1). BioMed Central. https://doi.org/10.24451/arbor.20860

Templ, M., & Sariyar, M. (2022). A systematic overview on methods to protect sensitive data provided for various analyses. In International Journal of Information Security (Vol. 21, Issue 6). Springer. https://doi.org/10.24451/arbor.18480

Kunz, S., Zgraggen, C., & Sariyar, M. (2022). Mapping SNOMED CT Codes to Semi-Structured Texts via an NLP Pipeline. In Studies in Health Technology and Informatics (Vol. 295). IOS Press. https://doi.org/10.24451/arbor.18475

Miletic, M., & Sariyar, M. (2022). The Sortal Concept in the Context of Biomedical Record Linkage. In Studies in Health Technology and Informatics (Vol. 295). IOS Press. https://doi.org/10.24451/arbor.18472

Miletic, M., & Sariyar, M. (2022). Explaining Contextualized Word Embeddings in Biomedical Research – A Qualitative Investigation. In Studies in Health Technology and Informatics (Vol. 295). IOS Press. https://doi.org/10.24451/arbor.18476

Adams, S., Uthayathas, G., & Sariyar, M. (2022). A Consent Tool for Secondary Use of Biomedical Data. In Studies in Health Technology and Informatics (Vol. 292). IOS Press. https://doi.org/10.24451/arbor.18477

Sariyar, M. (2022). Death from the Perspective of Luhmann’s System Theory. In Open Theology (Vol. 8, Issue 1). De Gruyter. https://doi.org/10.24451/arbor.18481

Abu Baker, M., Sariyar, M., Holm, J., & Calderara, F. (2022). Pro-Active Detection of Potentially Wrong Diagnoses Due to Substantial Changes of Laboratory Measurements. In Studies in Health Technology and Informatics (Vol. 289). IOS Press. https://doi.org/10.24451/arbor.18474

Neuenschwander, S., Romao, P., Holm, J., & Sariyar, M. (2022). Developing an Ontology for Documenting Adverse Events While Avoiding Pitfalls. In Studies in Health Technology and Informatics (Vol. 289). IOS Press. https://doi.org/10.24451/arbor.18478

Sariyar, M., & Holm, J. (2022). Embedding Risk-Based Anonymization into Data Access Control for Providing Individual-Level Health Data in a Secure Way. In Studies in Health Technology and Informatics (Vol. 289). IOS Press. https://doi.org/10.24451/arbor.18473

Sariyar, M., & Holm, J. (2022). Medical Informatics in a Tension Between Black-Box AI and Trust. In Studies in Health Technology and Informatics (Vol. 289). IOS Press. https://doi.org/10.24451/arbor.18479