Mehrdad Rakaee
Job description
- Medlem av Translasjonell kreftforskningsgruppe.
- Veileder for phd- og postdoc-studenter.
- Lang erfaring innen eksperimentell, statistisk, og beregnings analyse av kreft, med forskningsekspertise innen biomarkør utvikling, validering, klinisk implementering, klinikogenomikk, og kunstig intelligens-basert patologi.
- Hovedstilling som forsker I ved Avdeling for Klinisk Patologi, Universitetssykehuset Nord-Norge, Tromsø, med ansvar for å implementere, analysere, og tolke neste generasjons sekvensering (NGS) i rutinepraksis. Tjener også som genetiker i nasjonal infrastruktur for presisjonsdiagnostikk innen kreftbehandling (InPred), IMPRESS-Norway, og TNM-I kliniske studier for persontilpasset medisin.
- Bistilling som seniorforsker ved Åslaug Helland lab, Kreftgenetikk avdeling, Institutt for kreftforskning, Oslo universitetssykehus (OUS), med oppgaver som utvikling av kunstig intelligens-baserte verktøy som prediktive biomarkører for presisjons-immunterapi i lungekreft.
- Samarbeidspartner (affiliate) med Brigham and Women’s Hospital, Dana Farber Cancer Institute, Harvard Medical School, Boston, USA.
- Samarbeidspartner med Imperial College London, UK.
Amin H Nassar,
Elias Bou Farhat,
Hassan Abushukair,
Michel Alchoueriy,
Samer Salem,
Marc Machaalani
et al.:
Molecular and clinical insights of trastuzumab deruxtecan efficacy in advanced breast cancer
Falah Jabar Rahim,
Lill-Tove Rasmussen Busund,
Biagio Ricciuti,
Masoud Tafavvoghi,
Thomas Karsten Kilvær,
David J. Pinato
et al.:
Fully Automatic Content-Aware Tiling Pipeline for Pathology Whole Slide Images
Amin H. Nassar,
Chul Kim,
Tolulope Adeyelu,
Elias Bou Farhat,
Hassan Abushukair,
Mehrdad Rakaee
et al.:
Integrated molecular and clinical characterization of pulmonary large cell neuroendocrine carcinoma
Dagny Førde,
Thomas Karsten Kilvær,
Mona Irene Pedersen,
Ana Paola Lombardi,
Irene D’arsiè,
Erna-Elise Paulsen
et al.:
Prognostic impact of miR-17-5p and miR-20a-5p in NSCLC diverge in subgroups according to lymph node status
Bernhard Scheiner,
Pasquale Lombardi,
Antonio D’Alessio,
Gwangil Kim,
Masoud Tafavvoghi,
Oleksandr Petrenko
et al.:
Preliminary qualification of a machine learning-based assessment of the tumor immune infiltrate as a predictor of outcome in patients with hepatocellular carcinoma treated with atezolizumab plus bevacizumab
Dagny Førde,
Thomas Karsten Kilvær,
Mona Irene Pedersen,
Egil Støre Blix,
Ilona Halva Urbarova,
Erna-Elise Paulsen
et al.:
High density of TCF1+ stem-like tumor-infiltrating lymphocytes is associated with favorable disease-specific survival in NSCLC
Mehrdad Rakaee,
Masoud Tafavvoghi,
Biagio Ricciuti,
Joao V Alessi,
Alessio Cortellini,
Fabrizio Citarella
et al.:
Deep Learning Model for Predicting Immunotherapy Response in Advanced Non-Small Cell Lung Cancer
Masoud Tafavvoghi,
Anders Sildnes,
Mehrdad Rakaee,
Nikita Shvetsov,
Lars Ailo Aslaksen Bongo,
Lill-Tove Rasmussen Busund
et al.:
Deep learning-based classification of breast cancer molecular subtypes from H&E whole-slide images
Csaba Kerepesi,
Hassan Mohammed Abushukair,
Biagio Ricciuti,
Amin H Nassar,
Elio Adib,
Joao V Alessi
et al.:
Association of Baseline Tumor-Specific Neoantigens and CD8+ T-Cell Infiltration With Immune-Related Adverse Events Secondary to Immune Checkpoint Inhibitors
Erna-Elise Paulsen,
Sigve Andersen,
Mehrdad Rakaee,
Mona Irene Pedersen,
Ana Paola Lombardi,
Mette Pøhl
et al.:
Impact of microvessel patterns and immune status in NSCLC: a non-angiogenic vasculature is an independent negative prognostic factor in lung adenocarcinoma
Lorenzo Nibid,
Carlo Greco,
Ermanno Cordelli,
Giovanna Sabarese,
Michele Fiore,
Charles Z. Liu
et al.:
Deep pathomics: A new image-based tool for predicting response to treatment in stage III non-small cell lung cancer
Mehrdad Rakaee,
Sigve Andersen,
K. Giannikou,
Erna-Elise Paulsen,
Thomas Karsten Kilvær,
Lill-Tove Rasmussen Busund
et al.:
Machine learning-based immune phenotypes correlate with STK11/KEAP1 co-mutations and prognosis in resectable NSCLC: a sub-study of the TNM-I trial
Biagio Ricciuti,
Arielle Elkrief,
Joao Alessi,
Xinan Wang,
Yvonne Li,
Hersh Gupta
et al.:
Clinicopathologic, Genomic, and Immunophenotypic Landscape of ATM Mutations in Non–Small Cell Lung Cancer
Donjeta Gjuka,
Elio Adib,
Kendra Garrison,
Jianfeng Chen,
Yuxue Zhang,
Wenjiao Li
et al.:
Enzyme-mediated depletion of methylthioadenosine restores T cell function in MTAP-deficient tumors and reverses immunotherapy resistance
Masoud Tafavvoghi,
Erna-Elise Paulsen,
Falah Jabar Rahim,
Sigve Andersen,
Ana Paola Lombardi,
Elin Richardsen
et al.:
51P Deep learning-based detection of non-angiogenic growth patterns in early-stage lung cancer
Falah Jabar Rahim,
P-C. Lee,
C. Yoo,
H.J. Chon,
J. Cheon,
M. Kudo
et al.:
206P Development of a machine-learning model on pre-treatment characteristics to predict long-term survivorship to atezolizumab plus bevacizumab in advanced hepatocellular carcinoma
Per Niklas Benzler Waaler,
Magdalena Solveig Robertsen,
Erna-Elise Paulsen,
Sigve Andersen,
Elin Richardsen,
Åslaug Helland
et al.:
21P Integration of genomic and clinical data for relapse prediction in early-stage non-small cell lung cancer
Masoud Tafavvoghi,
Falah Jabar Rahim,
Sigve Andersen,
Erna-Elise Paulsen,
A. Cortellini,
P. Lombardi
et al.:
219P Benchmarking state-of-the-art deep learning models for tumor-infiltrating lymphocytes (TILs) quantification
Mehrdad Rakaee,
Per Niklas Benzler Waaler,
Falah Jabar Rahim,
Krinio Giannikou,
Elio Adib,
Sigve Andersen
et al.:
Abstract 5366: DRAGEN pipeline validation for somatic variant detection in diagnostics using TSO500 panel
Elias Bou Farhat,
Amin Nassar,
Hassan Mohammed Abushukair,
Michel Alchoueiry,
Samer Salem,
Marc Machaalani
et al.:
Molecular and clinical insights of trastuzumab deruxtecan efficacy in advanced breast cancer (aBC).
Masoud Tafavvoghi,
Elio Adib,
Elias Bou Farhat,
Falah Jabar Rahim,
Amin Nassar,
Åslaug Helland
et al.:
Single-slide histology-based deep learning model for mismatch repair deficiency prediction in colorectal cancer.
Mehrdad Rakaee,
Solfrid Thunold,
Masoud Tafavvoghi,
Åsa Kristina Öjlert,
Krinio Giannikou,
Elio Adib
et al.:
Multiomics profiling for prediction of immunotherapy response in advanced pleural mesothelioma: Sub-study of the NIPU trial.
Solfrid Thunold,
Mehrdad Rakaee,
K. Giannikou,
Eivor Hernes,
Saima Jamil Farooqi,
Å.K. Öjlert
et al.:
2977P Dual-time-point [18F] FDG PET/CT and tumour microenvironment features in pleural mesothelioma patients receiving immunotherapy
Mehrdad Rakaee
:
Pathology Foundation Models for Molecular and IO prediction
Mehrdad Rakaee
:
AI In Computational Pathology for Predicting Immunotherapy Outcomes
Mehrdad Rakaee
:
Revealing immune response and resistance through spatial profiling of NSCLC microenvironment
03. September 2025 ARKIV
Mehrdad Rakaee
:
Deep learning model for predicting immunotherapy response in patients with advanced NSCLC
Mehrdad Rakaee
:
Lovende biomarkør for immunterapi ved pleuramesoteliom
02. Juni 2025 ARKIV
Mehrdad Rakaee
:
Maskinlæring kan avgjøre når tester spriker om tarmkreftbehandling
01. Juni 2025 ARKIV
Mehrdad Rakaee
:
Priser til fremragende forskere ved Oslo universitetssykehus 2025 - Oslo universitetssykehus HF
06. Juni 2025 ARKIV
Mehrdad Rakaee
:
Priser til fremragende forskningsartikler publisert høsten 2024 - Oslo universitetssykehus HF
28. Mai 2025 ARKIV
Mehrdad Rakaee
:
AI Model Predicts Immunotherapy Response in Advanced Lung Cancer Patients | Managed Healthcare Executive
08. Januar 2025 ARKIV
M.S. Robertsen,
Per Niklas Benzler Waaler,
Sigve Andersen,
Erna-Elise Paulsen,
Thomas Karsten Kilvær,
Sissel Gyrid Freim Wahl
et al.:
1802P Tissue tumor mutational burden and risk of recurrence in early-stage non-small cell lung cancer
A.H. Nassar,
E. Bou Farhat,
N. Ghandi,
E. Adib,
Mehrdad Rakaee,
K. Raghav
et al.:
PT2.14.05 Redefining Clinical Outcomes for Peritoneal Mesothelioma (PeM) in the Era of Immunotherapy
E. Gariazzo,
A. Elkrief,
K. Concannon,
D. Ognissanti,
A. Dodi,
V. Favorito
et al.:
PT2.11.01 Predictors of Response to PD-(L)1 Blockade in Patients With Oncogene-Driver Negative NSCLC Without History of Tobacco Use
Mehrdad Rakaee,
Masoud Tafavvoghi,
A. Cortellini,
Sigve Andersen,
Falah Jabar Rahim,
L. Brunetti
et al.:
P1.11.62 Deep Learning Histopathology Model for PD-L1 (TPS) and Immunotherapy Outcome Prediction in Non-Small Cell Lung Cancer
Elio Adib,
falah jabar,
Masoud Tafavvoghi,
Amin Nassar,
Elias Bou Farhat,
Harvey J. Mamon
et al.:
Deep learning–powered analysis of tumor-infiltrating lymphocytes (TILs) in colorectal cancer
Mehrdad Rakaee
:
Existing biomarkers predicting ICI treatment response in advanced NSCLC - OncoDaily
29. Dezember 2024 ARKIV
Mehrdad Rakaee
:
Young Researcher of 2024 at Onkologisk Forum
21. November 2024 ARKIV
Mehrdad Rakaee
:
Immune Infiltration in the Tumor Microenvironment May Affect the Efficacy of Immunotherapy
21. November 2024 ARKIV
Mehrdad Rakaee
:
Tumormikromiljø og effekt av immunterapi
Elio Adib,
falah jabar,
Masoud Tafavvoghi,
Amin Nassar,
Lill-Tove Rasmussen Busund,
Tom Dønnem
et al.:
Artificial Intelligence-powered analysis of the tumor immune microenvironment in primary and metastatic colorectal cancer
Falah Jabar Rahim,
Sigve Andersen,
Erna-Elise Paulsen,
Masoud Tafavvoghi,
Elin Helmine Richardsen,
Sissel Gyrid Freim Wahl
et al.:
Integrating Artificial intelligence (AI)-based lymphocytic infiltration assessment in early-stage NSCLC: A sub-study of the TNM-I trial
Mehrdad Rakaee
:
Machine learning and AI in pathology for prediction of response to immunotherapy
2024 ARKIV
Elio Adib,
Mehrdad Rakaee,
Amin Nassar,
Elias Bou Farhat,
Stephen Hodi,
David J. Kwiatkowski
:
Machine learning (ML)-based quantification of tumor-infiltrating lymphocytes (TIL) and clinical outcomes of patients with melanoma treated with immune-checkpoint inhibitors (ICI)
Mehrdad Rakaee
:
Stian har livstruende lungekreft: – Jeg er beviset på at forskning nytter
08. Juni 2023 ARKIV
Mehrdad Rakaee,
Masoud Tafavvoghi,
Elio Adib,
Biagio Ricciuti,
Joao Alessi,
Alessio Cortellini
et al.:
Artificial intelligence algorithm developed to predict immune checkpoint inhibitors efficacy in non–small-cell lung cancer
Scheiner Bernhard,
Alessio Antonio,
Kim Gwangil,
D. Goldin Robert,
A.M. Fulgenzi Claudia,
Balcar Lorenz
et al.:
MACHINE LEARNING-BASED ASSESSMENT OF TUMOUR- INFILTRATING LYMPHOCYTES PREDICTS OUTCOMES IN PATIENTS WITH HEPATOCELLULAR CARCINOMA UNDERGOING ATEZOLIZUMAB AND BEVACIZUMAB TREATMENT
2023 ARKIV
Mehrdad Rakaee,
Patrick Holmstad
:
Mutational drivers of a dysfunctional local immune response in resected non-small cell lung cancer (NSCLC) patients
UiT Norges arktiske universitet 30. Mai 2023 ARKIV
Mehrdad Rakaee,
Siri Kristoffersen
:
Developing a machine learning model for tumor cell quantification in standard histology images of lung cancer
UiT Norges arktiske universitet 31. Mai 2023 ARKIV
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Research interests
- Kunstig Intelligens (AI) i digital patologi
- Kreftimmunterapi
- Persontilpasset onkologi