Iannis Drakos, PhD
Data & Informatics Scientist, Department Head, Department of Big Data and Personalized Surgery (DPS)
Center for Surgical Science (CSS)
Iannis is a data and informatics scientist (BSc, MSc, 2000, School of Engineering) with a PhD in Medicine and Machine Learning (“Prognosis, diagnosis and treatment of malignant lymphomas using Artificial Intelligence”, 2009, School of Medicine). Iannis is a pioneer of precision medicine with his work focusing around biomedical data integration, analysis and biomedical predictions from his graduation days, back to 2000.
He has successfully served via senior roles numerous national, European and international research projects, clinical trials and educational activities. His work includes 1st time solutions to open problems, contribution to open-source projects and using machine learning to translate health data into improved healthcare services.
Iannis has been teaching data science to under- and post-graduate medical students for more than 10 years, with his book chapters on health databases (Efficient Database Design) and cloud computing (Web Delivered Interactive Applications) being part of the teaching portfolio of US Medical Schools.
Past projects where Iannis was involved were aiming to improve data integration (mainly clinical/phenotypic with OMICs), cross-analysis, and AI driven biomarker discovery.
Currently, he is heading the Department of Big Data and Personalized Surgery (DPS) at the Center for Surgical Science in Denmark. DPS is utilizing the OMOP CDM and the OHDSI community tools to unify heterogeneous data and unleash the full power of machine learning to the complete spectrum of health data. The main target of DPS is to translate health data into improved diagnosis, prognosis and treatment for the benefit of the patient and the healthcare professional.
- Clinical and multi-omics cross-phenotyping of patients with autoimmune and autoinflammatory diseases: the observational TRANSIMMUNOM protocol. Lorenzon R, Mariotti-Ferrandiz E, Aheng C, Ribet C, Toumi F, Pitoiset F, Chaara W, Derian N, Johanet C, Drakos I, Harris S, Amselem S, Berenbaum F, Benveniste O, Bodaghi B, Cacoub P, Grateau G, Amouyal C, Hartemann A, Saadoun D, Sellam J, Seksik P, Sokol H, Salem JE, Vicaut E, Six A, Rosenzwajg M, Bernard C, Klatzmann D. BMJ Open 2018;8:e021037. doi: 10.1136/bmjopen-2017-021037.
- Web Delivered Interactive Applications. Drakos J. Informatics in Medical Imaging. Published October 17th, 2011 by CRC Press, USA.
- Efficient Database Design. Drakos J. Informatics in Medical Imaging. Published October 17th, 2011 by CRC Press, USA.
- Bayesian clustering of flow cytometry data for the diagnosis of B-Chronic Lymphocytic Leukemia. Lakoumentas, J. Drakos, J. Karakantza, M. Nikiforidis, G. Sakellaropoulos, G. Journal of Biomedical Informatics, 2009;42:251-261.
- A perspective for biomedical data integration: Design of databases for Flow Cytometry. Drakos, J. Karakantza, M. Zoumbos, N. Lakoumentas, J. Nikiforidis, G. Sakellaropoulos, G. BMC Bioinformatics (Volume 9, 14/2/2008, article number 99).