Parisa Movahedi
Doctoral Student, Department of Computing.
parmov@utu.fi : 452B |
Machine learning, Data analysis, Artificial intelligence, Medical image processing
Parisa movahedi is a Ph.D. candidate and a project researcher at the University of Turku, Finland. She received here M.Sc. (Tech) degree in information and communications technology at the university of Turku, Finland. Her main research interest include machine learning model development and evaluation of Non-i.i.d data and privacy preserving AI for health data.
For the last 8 years, Parisa has been working in several projects and collaborated with different institutes (Helsinki university, medical imaging center for southwest Finland, Turku university hospital (TYKS)) specializing in machine learning applicability and performance evaluation. Currently she is a part of the PRIVASA group, researching different areas of privacy preserving AI for health data.
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- Response to Commentary by Dehaene et al. on Synthetic Discovery is not only a Problem of Differentially Private Synthetic Data (2025)
- Methods of Information in Medicine
- Benchmarking Evaluation Protocols for Classifiers Trained on Differentially Private Synthetic Data (2024)
- IEEE Access
- Does Differentially Private Synthetic Data Lead to Synthetic Discoveries? (2024)
- Methods of Information in Medicine
- Finnish perspective on using synthetic health data to protect privacy: the PRIVASA project (2024)
- Applied Computing and Intelligence
- Targeted and Untargeted Amine Metabolite Quantitation in Single Cells with Isobaric Multiplexing (2024)
- Chemistry - A European Journal
- Evaluating Classifiers Trained on Differentially Private Synthetic Health Data (2023)
- Proceedings (IEEE International Symposium on Computer-Based Medical Systems)
- Long-Term Autonomy in Forest Environment Using Self-Corrective SLAM (2022) New Developments and Environmental Applications of Drones: Proceedings of FinDrones 2020 Nevalainen Paavo, Movahedi Parisa, Peña Queralta Jorge, Westerlund Tomi, Heikkonen Jukka
- GeFeS: A generalized wrapper feature selection approach for optimizing classification performance (2020)
- Computers in Biology and Medicine
- Prediction of prostate cancer aggressiveness using 18 F-Fluciclovine (FACBC) PET and multisequence multiparametric MRI (2020)
- Scientific Reports
- Comparative Analysis of Image Fusion Methods in Marine Environment (2019) 2019 IEEE International Symposium on Robotic and Sensors Environments (ROSE) Fahimeh Farahnakian, Parisa Movahedi, Jussi Poikonen, Eero Lehtonen, Dimitrios Makris, Jukka Heikkonen
- Luminometric label array for quantification of metal ions in drinking water – Comparison to human taste panel (2019)
- Microchemical Journal
- Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization (2019)
- PLoS ONE
- Combined transcriptomics, proteomics and metabolomics analysis identifies metabolic pathways associated with the loss of cardiac regeneration (2018)
- Cardiovascular Research
- Molecular atlas of postnatal mouse heart development (2018)
- Journal of the American Heart Association
- Time-Gated Raman Spectroscopy for Quantitative Determination of Solid-State Forms of Fluorescent Pharmaceuticals (2018)
- Analytical Chemistry
- Fitting methods for intravoxel incoherent motion imaging of prostate cancer on region of interest level: Repeatability and gleason score prediction (2017)
- Magnetic Resonance in Medicine
- Diffusion Weighted Imaging of Prostate Cancer: Prediction of Cancer using Texture Features from Parametric Maps of the Monoexponential and Kurtosis functions (2016) 2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA) Ileana Montoya Perez, Jussi Toivonen, Parisa Movahedi, Harri Merisaari, Marko Pesola, Pekka Taimen, Peter J. Boström, Aida Kiviniemi, Hannu J. Aronen, Tapio Pahikkala, Ivan Jambor
- Diffusion weighted imaging of prostate cancer xenografts: comparison of bayesian modeling and independent least squares fitting (2016)
- International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition. Proceedings
- Fast regularized least squares and k-means clustering method for intrusion detection systems (2015) Proceedings of the International Conference on Pattern Recognition Applications and Methods Parisa Movahedi, Paavo Nevalainen, Markus Viljanen, Tapio Pahikkala
- Improving waveform quality in direct power control of DFIG using fuzzy controller (2015)
- Neural Computing and Applications
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