Andreychenko Anna

Head of the Artificial Intelligence department

Project role

Development of technologies for automatic processing, data analysis, construction of predictive models on the Webiomed platform, including the usage of artificial intelligence technologies.

Education

  • Ph.D., 2013, Faculty of Medicine, University of Utrecht, the Netherlands
  • Master of Science, 2009, Radbau University, The Netherlands
  • Specialist in Medical Physics, 2008, National Research Nuclear University “MEPhI”, Russia

Professional achievements

In 2019-2020: It was developed a methodology for measurements, testing and educational services based on artificial intelligence for radiation diagnostics and practically implemented within the framework of the scientific and practical “Experiment on the use of effective technologies in computer vision for the analysis of medical images and further application in the healthcare system of the city of Moscow.”

In 2020-2021 tools were created for technological support of the scientific and practical “Experiment on the use of innovative technologies in the field of computer vision for the analysis of medical images and further application in the healthcare system of the city of Moscow”: 1) Medlabel-automated analysis of medical protocols; 2) Dashboard for monitoring the performance of services based on artificial intelligence in healthcare; 3) Platform for automated testing of the accuracy of AI algorithms in the process of their evolution; 4) Methodology for creating reference medical data sets for validating artificial intelligence and machine learning algorithms.

A methodology and an online tool were developed and three “AI battles” were conducted in 2019, 2020, 2021. - unique open competitions to compare finished AI products for radiation and instrumental diagnostics with doctors. In 2020, more than 12 thousand markings of radiological studies were collected from 188 specialists in the Russian Federation and the CIS countries.

From 2017 to 2019 a targeted clinical magnetic resonance imaging (MRI) technique was developed and demonstrated for breast MRI using a unique wireless device based on metamaterials.

In 2013-2018 approaches and tools have been developed for automatic processing and analysis of physiological signals and images collected during magnetic resonance imaging in order to extract quantitative biomarkers of pathologies, improve the quality of extracted diagnostic information, and personalize therapy.

From 2014 to 2017  she took part in the introduction into clinical practice of the world's first experimental device for delivering radiation therapy with simultaneous imaging using high-field MRI (MRLinac).

In 2009-2012 the technology for conducting clinical ultra-high-field MRI (7 Tesla) of the human body has been developed and tested, as well as an improved technology for studying the biochemical composition of human brain tissue in vivo.

Research

She got the degree of Doctor of Philosophy In 2013. The topic was “Radiofrequency solutions for clinical ultra-high-field magnetic resonance imaging.” This work was carried out at the University Hospital of Utrecht and at the Faculty of Medicine of the University of Utrecht in the Netherlands.

She has more than 80 publications in international journals ( more than 30 are in Q1-level ) and abstracts of prestigious conferences. They are Nature Communication, NeuroImage: Clinical, IEEE Transactions on Medical Imaging, Magnetic Resonance in Medicine, etc. Also she has 7 patents and others registered intellectual property rights.

She took part in more than 100 international scientific and popular science events as a speaker, moderator and co-organizer (“Society for Imaging Informatics in Medicine”, “International Society of Magnetic Resonance in Medicine”, “European congress of radiology”, “European Society for Magnetic Resonance in Medicine and Biology”, “American Association of Physicists in Medicine”, “European Society of Medical Imaging Informatics”, “Healthy Moscow” Assembly, “RORR”, “Congresses of the MRO RORR”, etc.)

Now she is a member of the editorial board and reviewer of scientific journals “Digital Diagnostics”, “Magnetic Resonance in Medicine”, “Journal of Applied Physics”, “NMR in Biomedicine”. member of scientific professional communities International Society for Magnetic Resonance in Medicine (ISMRM), European Society for Magnetic Resonance in Medicine and Biology (ESMRMB), European Society of Medical Imaging Informatics (EuSoMII) .deputy Head of the Committee on AI in Radiation Diagnostics of the professional society "Moscow Regional Branch of the Russian Society of Radiologists and Radiologists".

Recent publications

  • Vladzymyrskyy, A., Arzamasov, K., Gelezhe, P., Morozov, S., Ledikhova, N., Andreychenko, A., ... & Bondarchuk, D. (2023). DIAGNOSTIC ACCURACY OF ARTIFICIAL INTELLIGENCE FOR ANALYSIS OF 1.3 MILLION MEDICAL IMAGING STUDIES: THE MOSCOW EXPERIMENT ON COMPUTER VISION TECHNOLOGIES. medRxiv, 2023-08
  • Vasilev, Yuriy, et al. "Clinical application of radiological AI for pulmonary nodule evaluation: Replicability and susceptibility to the population shift caused by the COVID-19 pandemic." International Journal of Medical Informatics 178 (2023): 105190.
  • Zinchenko, V., Chetverikov, S., Akhmad, E. et al. Changes in software as a medical device based on artificial intelligence technologies. Int J CARS (2022). https://doi.org/10.1007/s11548-022-02669-1
  • Nagaraj Y, de Jonge G, Andreychenko A, Presti G, Fink MA, Pavlov N, Quattrocchi CC, Morozov S, Veldhuis R, Oudkerk M, van Ooijen PMA. Facilitating standardized COVID-19 suspicion prediction based on computed tomography radiomics in a multi-demographic setting. Eur Radiol. 2022 Apr 1:1–13. doi: 10.1007/s00330-022-08730-6. Epub ahead of print. PMID: 35362751; PMCID: PMC8973680.
  • Morozov S.P., Andreychenko A.E., Blokhin I.A., Gelezhe P.B., Gonchar A.P., Nikolaev A.E., Pavlov N.A., Chernina V.Y., Gombolevskiy V.A. MosMedData: data set of 1110 chest CT scans performed during the COVID-19 epidemic // Digital Diagnostics. - 2020. - Vol. 1. - N. 1. - P. 49-59. doi: 10.17816/DD46826 
  • Brui E, Efimtcev AY, Fokin VA, Fernandez R, Levchuk AG, Ogier AC, Samsonov AA, Mattei JP, Melchakova IV, Bendahan D, Andreychenko A. Deep learning-based fully automatic segmentation of wrist cartilage in MR images. NMR Biomed. 2020 Aug;33(8):e4320. doi: 10.1002/nbm.4320. Epub 2020 May 11. PMID: 32394453; PMCID: PMC7784718. 
  • Shchelokova, A., Ivanov, V., Mikhailovskaya, A. et al. Ceramic resonators for targeted clinical magnetic resonance imaging of the breast. Nat Commun 11, 3840 (2020). https://doi.org/10.1038/s41467-020-17598-3 
  • Anouk Marsman, René C.W. Mandl, Dennis W.J. Klomp, Marc M. Bohlken, Vincent O. Boer, Anna Andreychenko, Wiepke Cahn, René S. Kahn, Peter R. Luijten, Hilleke E. Hulshoff Pol, GABA and glutamate in schizophrenia: A 7 T 1H-MRS study, NeuroImage: Clinical, Volume 6, 2014, Pages 398-407, ISSN 2213-1582, https://doi.org/10.1016/j.nicl.2014.10.005.

Main area of ​​professional interest

Artificial intelligence, machine learning and big data technologies in medicine and healthcare. Medical images and diagnostics. Medical physics. Radiation therapy

SPIN-код:
6625-4186

AuthorID:
1038517

Scopus author ID:
57208582302

Web of Science ResearcherID:
E-4930-2017

ORCID:
0000-0001-6359-0763

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