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Mehrad Mahmoudian

- Project Researcher,
Institute of Biomedicine (Faculty of Medicine)
- Doctoral Researcher,
Department of Computing (Faculty of Technology)

mehmah@utu.fi

Tykistökatu 6

Turku

: https://orcid.org/0000-0001-7650-1862

Statistical Data Analysis, Survival Analysis, Machine Learning

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A predictive model of overall survival in patients with metastatic castration-resistant prostate cancer (2017)
- F1000Research
Mehrad Mahmoudian, Fatemeh Seyednasrollah, Liisa Koivu, Outi Hirvonen, Sirkku Jyrkkiö, Laura L. Elo
How Reliable are Trial-based Prognostic Models in Real-world Patients with Metastatic Castration-resistant Prostate Cancer? (2017)
- European Urology
Fatemeh Seyednasrollah, Mehrad Mahmoudian, Liisa Rautakorpi, Outi Hirvonen, Tarja Laitinen, Sirkku Jyrkkiö, Laura L. Elo
Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data (2017)
- Lancet Oncology
Guinney J, Wang T, Laajala TD, Winner KK, Bare JC, Neto EC, Khan SA, Peddinti G, Airola A, Pahikkala T, Mirtti T, Yu T, Bot BM, Shen L, Abdallah K, Norman T, Friend S, Stolovitzky G, Soule H, Sweeney CJ, Ryan CJ, Scher HI, Sartor O, Xie Y, Aittokallio T, Zhou FL, Costello JC, and the Prostate Cancer Challenge DREAM Community
Reply to Tuomas Mirtti and Tero Aittokallio's Letter to the Editor re: Fatemeh Seyednasrollah, Mehrad Mahmoudian, Liisa Rautakorpi, et al. How Reliable are Trial-based Prognostic Models in Real-world Patients with Metastatic Castration-resistant Prostate Cancer? Eur Urol. 2017;71:838-40. Clinical Utility of Trial-estimated Prognostic Models. (2017)
- European Urology
Seyednasrollah F, Mahmoudian M, Rautakorpi L, Hirvonen O, Laitinen T, Jyrkkiö S, Elo LL