Ileana Montoya Perez profile picture
Ileana
Montoya Perez
Senior Researcher, Data analytics
MSc. in Information Technology
Data analysis and performance evaluation with challenging data sets: prostate cancer as a case study. A close collaboration between Depts. of Computing (UTU), Radiology and Urology (TYKS).

Contact

Links

ResearchGate profile
GoogleScholar
CV.pdf
ORCID

Areas of expertise

Data analysis
Machine learning
Statistics
Databases
Web-development

Biography

MSc. Ileana Montoya Perez, a Ph.D. candidate and project researcher in computer science at the University of Turku (UTU), graduated as a Systems and computer engineer in 2000, worked as a software developer for the industry, and in education as an ICT coordinator for over ten years. She received her master’s degree in Information Technology in April 2014 from UTU. Since May 2014, she has worked as a web developer on an interdisciplinary project between Dept. of Urology (TYKS) and the Dept. of Computing (UTU), designing and building databases and web applications to collect and present retrospective data for bladder and prostate cancer research. At the same time, she started her research on machine learning methods for performance evaluation when the available data is limited and challenging. This research has been active collaboration between the Dept. of Computing, Dept. of Radiology, and Dept. of Urology. Since the start of 2021, she is been part of the PRIVASA group, researching the technical aspect of privacy-preserving of artificial intelligence (AI) for synthetic and anonymous health data.

Teaching

Areas of interest in teaching are data analysis and machine learning, especially performance evaluation methods. 

Research

Currently working on two research areas: Data analysis and performance evaluation with challenging data sets: prostate cancer as a case study, and privacy-preservation of AI for synthetic and anonymous health data. The former aims to develop, apply, and evaluate machine learning methods to combinations of clinical variables, kallikreins, and magnetic resonance imaging (MRI) parameters for detecting and characterizing prostate tumors, while the latter aims to evaluate and develop techniques for preserving the privacy of health data by generating differentially private synthetic data or by applying differential privacy to study statistics to maintain participants' privacy. 

Publications

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Predicting the Need for Biopsy to Detect Clinically Significant Prostate Cancer in Patients with a Magnetic Resonance Imaging–detected Prostate Imaging Reporting and Data System/Likert ≥3 Lesion: Development and Multinational External Validation of the Imperial Rapid Access to Prostate Imaging and Diagnosis Risk Score (2022)

European Urology
Peters Max, Eldred-Evans David, Kurver Piet, Falagario Ugo Giovanni, Connor Martin J., Shah Taimur T., Verhoeff Joost J.C., Taimen Pekka, Aronen Hannu J., Knaapila Juha, Montoya Perez Ileana, Ettala Otto, Stabile Armando, Gandaglia Giorgio, Fossati Nicola, Martini Alberto, Cucchiara Vito, Briganti Alberto, Lantz Anna, Picker Wolfgang, Haug Erik Skaaheim, Nordström Tobias, Tanaka Mariana Bertoncelli, Reddy Deepika, Bass Edward, van Rossum Peter S.N., Wong Kathie, Tam Henry, Winkler Mathias, Gordon Stephen, Qazi Hasan, Boström Peter J., Jambor Ivan, Ahmed Hashim U.
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )

Individualised non-contrast MRI-based risk estimation and shared decision-making in men with a suspicion of prostate cancer: protocol for multicentre randomised controlled trial (multi-IMPROD V.2.0) (2022)

BMJ Open
Ettala Otto, Jambor Ivan, Perez Ileana Montoya, Seppänen Marjo, Kaipia Antti, Seikkula Heikki, Syvänen Kari T, Taimen Pekka, Verho Janne, Steiner Aida, Saunavaara Jani, Saukko Ekaterina, Löyttyniemi Eliisa, Sjoberg Daniel D, Vickers Andrew, Aronen Hannu, Boström Peter
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Detection of Prostate Cancer Using Biparametric Prostate MRI, Radiomics, and Kallikreins: A Retrospective Multicenter Study of Men With a Clinical Suspicion of Prostate Cancer (2021)

Journal of Magnetic Resonance Imaging
Perez Ileana Montoya, Merisaari Harri, Jambor Ivan, Ettala Otto, Taimen Pekka, Knaapila Juha, Kekki Henna, Khan Ferdhos L, Syrjälä Elise, Steiner Aida, Syvänen Kari T, Verho Janne, Seppänen Marjo, Rannikko Antti, Riikonen Jarno, Mirtti Tuomas, Lamminen Tarja, Saunavaara Jani, Falagario Ugo, Martini Alberto, Pahikkala Tapio, Pettersson Kim, Boström Peter J, Aronen Hannu J
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Combined Use of Prostate-specific Antigen Density and Magnetic Resonance Imaging for Prostate Biopsy Decision Planning: A Retrospective Multi-institutional Study Using the Prostate Magnetic Resonance Imaging Outcome Database (PROMOD). (2021)

European Urology Oncology
Falagario UG, Jambor I, Lantz A, Ettala O, Stabile A, Taimen P, Aronen HJ, Knaapila J, Perez IM, Gandaglia G, Fossati N, Martini A, Cucchiara V, Picker W, Haug E, Haines K, Ratnani P, Sujit N, Lewis S, Sanguedolce F, Selvaggio O, Cormio L, Macarini L, Tewari A, Nordström T, Boström PJ, Briganti A, Carrieri G
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Negative Predictive Value of Biparametric Prostate Magnetic Resonance Imaging in Excluding Significant Prostate Cancer: A Pooled Data Analysis Based on Clinical Data from Four Prospective, Registered Studies (2021)

European Urology Focus
Juha Knaapila, Ivan Jambor, Otto Ettala, Pekka Taimen, Janne Verho, Ileana Montoya Perez, Aida Kiviniemi, Tapio Pahikkala, Harri Merisaari, Tarja Lamminen, Jani Saunavaara, Hannu J.Aronen, Kari T.Syvänen, Peter J.Boström
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Prostate Cancer Risk Stratification in Men With a Clinical Suspicion of Prostate Cancer Using a Unique Biparametric MRI and Expression of 11 Genes in Apparently Benign Tissue: Evaluation Using Machine-Learning Techniques (2020)

Journal of Magnetic Resonance Imaging
Ileana Montoya Perez, Ivan Jambor, Tapio Pahikkala, Antti Airola, Harri Merisaari, Jani Saunavaara, Saeid Alinezhad, Riina-Minna Väänänen, Terhi Tallgrén, Janne Verho, Aida Kiviniemi, Otto Ettala, Juha Knaapila, Kari T. Syvänen, Markku Kallajoki, Paula Vainio, Hannu J. Aronen, Kim Pettersson, Peter J. Boström, Pekka Taimen
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))
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