Mattias Rantalainen
Senior Lecturer
| Docent
E-mail: mattias.rantalainen@ki.se
Telephone: +46852482465
Visiting address: ,
Postal address: C8 Medicinsk epidemiologi och biostatistik, C8 MEB II Rantalainen, 171 77 Stockholm
About me
- The Predictive Medicine group focus on medical research that is driven by
statistical machine learning, artificial intelligence and big data. Currently
our main focus is on computational pathology.
I am an associate professor (docent) at the Department of Medical
Epidemiology and Biostatistics where I lead the Predictive Medicine group.
I was previously a research fellow (2009-2013) with a joint affiliation at
the Department of Statistics (University of Oxford) and at the Wellcome Trust
Centre for Human Genetics (University of Oxford) where I worked with
Professor Chris Holmes and Dr. Cecilia Lindgren. I was awarded a MRC
Centenary Early Career Award (2012-2013) and a Medical Research Council (MRC)
Special Training Fellowship in Biomedical Informatics (2009-2012). I had a
postdoctoral position working on the data analysis work package for the
MolPAGE consortium in Prof Chris Holmes’ group at the Department of
Statistics in Oxford (2008). I completed my PhD at Imperial College London
where I developed novel multivariate pattern recognition methods with
applications in metabonomics, working together with Professor Elaine Holmes
and Professor Jeremy Nicholson. I have an undergraduate degree in
Engineering Biology (combined BSc/MSc) from Umeå University in Sweden.
Research
- *The Predictive Medicine group focus on medical research that is driven by
statistical machine learning, artificial intelligence (AI) and large
population representative data sets. Currently our research is centered on
projects in the computational pathology domain.*
We develop and apply statistical and machine learning methodologies for
predictive modelling in biomedical applications with a particular interest in
precision medicine and cancer research.
Our mission is to drive the development and application of data-driven
approaches in cancer precision medicine and to develop and validate novel
patient stratification models, including prognostic and treatment predictive
applications. To achieve this we develop methods and models that allow us to
transform large biomedical data into clinically relevant predictions at the
individual level. Some of our research is focused on clinical translation and
implementation.
Our research is based on large datasets (big-data) across multiple modalities
including comprehensive molecular profiling (e.g. DNA- and RNA-sequencing),
clinical information and medical imaging data (histopathology).
*Main research areas*
* *Computational pathology:* AI (deep learning) driven research focusing on
developing and validating models in the domain of cancer histopathology.
The research is based on large population representative studies (we have
> - 70, 000 WSIs collected in-house). The main focus is on breast, prostate
and colorectal cancer (www.chimestudy.se [1] & - www.abcap.org [2]). I
coordinate the Swedish AI Precision Pathology (SwAIPP) consortium,
focusing on translation and implementation of AI-based pathology
(www.swaipp.org [3])
* *Cancer precision medicine:* Development and validation of predictive
models for improved patient stratification, based on comprehensive
molecular phenotyping data (e.g. DNA- and RNA-sequencing)
*Current research grants (as PI)*
Our work is supported by Swedish Research Council (VR), Swedish Cancer
Society, ERA PerMed, MEDTECHLABS, VINNOVA, SWElife, SeRC and Karolinska
Institutet.
*Doctoral students*
* Philippe Weitz (main supervisor)
* Abhinav Sharma (main supervisor)
* Dusan Rasic (co-supervisor)
* Sandra Kristiane Sinius Pouplier (co-supervisor)
* Tewodros Yalew (co-supervisor)
* Quang Thinh Trac (co-supervisor)
* Venkatesh Chellappa Patel (co-supervisor)
* Xiaoyang Du (co-supervisor)
*Other group members*
* Yanbo Feng (Postdoc)
* Leslie Solorzano Vargas (Postdoc)
* Bojing Liu (Postdoc)
* Constance Boissin (Postdoc)
* Duong Tran (Project assistant)
* Yujie Xiang (Research assistant)
* Ariane Buckenmeyer (Research technician)
* Viktoria Sartor (MSc student)
*Former group members / supervised students*
* Yinxi Wang (PhD student, main supervisor)
* Peter Ström (PhD student, co-supervisor)
* Pablo Gonzalez Ginestet (PhD student, co-supervisor)
* Charlotte Von Heijne Widlund (visiting scientist)
* Mei Wang (Postdoc - currently Research Assistant Professor, School of life
science, Peking University, China)
* Arvind Mer (Postdoc, currently Assistant Professor, University of Ottawa,
Canada)
* Nghia Vu (Postdoc - currently Assistant Professor, Karolinska Institutet,
MEB)
* Daniel Garcia León (Postdoc)
* Astrid Helzen (Technician)
* Balasz Acs (Associated postdoc)
* Kajsa Ledesma Eriksson (MSc student)
* Sandy Kang Lövgren (MSc student)
* Anton Normelius (MSc student)
* Boxi Zhang (MSc student)
* Youcheng Zhang (MSc student)
*Examples of publications*
Wang Y, Acs B, Robertson S, Liu B, Solorzano L, Wählby C, Hartman J,
*Rantalainen M.* Improved breast cancer histological grading using deep
learning, Annals of Oncology. 2022 33 (1), 89-98
Wang Y, Kartasalo K, Valkonen M, Larsson C, Ruusuvuori P, Hartman J,
*Rantalainen M.* Predicting molecular phenotypes from histopathology images:
a transcriptome-wide expression-morphology analysis in breast cancer. Cancer
Research. 2021 81 (19), 5115-5126
Weitz P, Wang Y, Hartman J, *Rantalainen M*. An investigation of attention
mechanisms in histopathology whole-slide-image analysis for regression
objectives. In Proceedings of the IEEE/CVF International Conference on
Computer Vision 2021 (pp. 611-619).
Acs B, *Rantalainen M*, Hartman J., Artificial intelligence as the next step
towards precision pathology. Journal of Internal Medicine. 2020 Mar 3.
Liu B, Wang Y, Weitz P, Lindberg J, Egevad L, Grönberg H, Eklund M,
*Rantalainen M.* Using deep learning to detect patients at risk for prostate
cancer despite benign biopsies. iScience. 2022 25 (7) 104663
Weitz P, Wang Y, Kartasalo K, Egevad L, Lindberg J, Grönberg H, Eklund M,
*Rantalainen M.* Transcriptome-wide prediction of prostate cancer gene
expression from histopathology images using co-expression based convolutional
neural networks. Bioinformatics. 2022 38 (13), 3462-3469
Ström, P., Kartasalo, K., Olsson, H., Solorzano, L., Delahunt, B., Berney,
D.M., Bostwick, D.G., Evans, A.J., Grignon, D.J., Humphrey, P.A., Iczkowski,
K.A.. Kench, J.G., Kristiansen, G., van der Kwast, T.H., Leite, K.R.M.,
McKenneym, J.K., Oxley, J., Pan, C.C., Samaratunga, H., Srigley, J.R.,
Takahashi, H., Tsuzuki, T., Varma, M., Zhou, M., Lindberg, J., Lindeskog,
C., Ruusuvuori, P, Wählby, C., Grönberg, H., *Rantalainen, M.*, Egevad,
L., Eklund, M., Artificial intelligence for diagnosis and grading of
prostate cancer in biopsies: a population-based, diagnostic study. /The
Lancet Oncology/. 2020 Jan 8.
Wang, M., Lindberg, J., Klevebring, D., Nilsson, C., Lehmann, S., Grönberg,
H., *Rantalainen, M.*, Development and validation of a novel RNA
sequencing-based prognostic score for acute myeloid leukemia, J Natl Cancer
Inst, 2018 Mar 18
Vu, T.N., Wills, Q.F., Kalari, K.R., Niu, N., Wang, L., Pawitan,
Y., *Rantalainen M.*, Isoform-level gene expression patterns in single-cell
RNA-sequencing data, Bioinformatics, 2018 Feb 1
Wang, M., Klevebring, D., Lindberg, K., Czene, K., Grönberg,
H., *Rantalainen M.* - Determining breast cancer histological grade from RNA
sequencing data. Breast Cancer Research, 2016, 18(1).
Vu, N.T., Wills, Q.F., Kalari, K.R., Niu, N., Wang, L., *Rantalainen M.*§,
Pawitan Y.§. Beta-Poisson model for single-cell RNA-seq data analyses.
Bioinformatics, 2016, btw202.
[1] http://www.chimestudy.se
[2] http://www.abcap.org
[3] www.swaipp.org
Teaching
- * Course director, "Multivariate prediction modelling with applications in
precision medicine" [1].
[1] http://ki.se/en/meb/multivariate-prediction-modelling-with-applications-in-precision-medicine
Articles
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Article: BREAST CANCER RESEARCH. 2024;26(1):17
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Article: EUROPEAN JOURNAL OF CANCER. 2023;191:112953
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Article: SCIENTIFIC DATA. 2023;10(1):562
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Article: NPJ PRECISION ONCOLOGY. 2023;7(1):32
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Article: ISCIENCE. 2022;25(7):104663
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Article: BIOINFORMATICS. 2022;38(13):3462-3469
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Article: ANNALS OF ONCOLOGY. 2022;33(1):89-98
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Article: CANCER RESEARCH. 2021;81(19):5115-5126
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Article: BLOOD ADVANCES. 2021;5(4):1003-1016
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Article: NATURE COMMUNICATIONS. 2021;12(1):1054
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Article: BLOOD CANCER JOURNAL. 2020;10(6):67
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Article: LANCET ONCOLOGY. 2020;21(2):222-232
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Article: CLINICAL CANCER RESEARCH. 2019;25(6):1766-1773
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Article: GENOME MEDICINE. 2018;10(1):85
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Article: JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE. 2018;110(10):1094-1101
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Article: JOURNAL OF CLINICAL PATHOLOGY. 2018;71(9):787-794
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Article: BIOINFORMATICS. 2018;34(14):2392-2400
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Article: BRIEFINGS IN FUNCTIONAL GENOMICS. 2018;17(4):273-282
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Article: HISTOPATHOLOGY. 2018;72(6):974-989
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Article: JOURNAL OF HEMATOLOGY & ONCOLOGY. 2018;11(1):52
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Article: BMC CANCER. 2017;17(1):802
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Article: LEUKEMIA. 2017;31(10):2029-2036
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Article: JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION. 2017;24(5):950-957
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Article: CANCER RESEARCH. 2017;77(13):3708-3717
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Article: CLINICAL CANCER RESEARCH. 2017;23(10):2584-2592
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Article: SCIENTIFIC REPORTS. 2016;6:38037
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Article: BIOINFORMATICS. 2016;32(14):2128-2135
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Article: CELL REPORTS. 2016;15(9):2000-2011
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Article: BREAST CANCER RESEARCH. 2016;18(1):48
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Article: MODERN PATHOLOGY. 2016;29(4):318-329
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Article: SCIENTIFIC REPORTS. 2016;6:20200
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Article: JOURNAL OF ALZHEIMERS DISEASE. 2015;45(4):1061-1076
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Article: JOURNAL OF PROTEOME RESEARCH. 2015;14(1):479-490
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Article: METHODS IN MOLECULAR BIOLOGY. 2015;1277:147-159
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Article: PLOS ONE. 2015;10(5):e0127882
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Article: METABOLOMICS. 2014;10(2):280-290
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Article: PLOS ONE. 2013;8(2):e55923
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Article: JOURNAL OF PROTEOME RESEARCH. 2012;11(9):4712-4721
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Article: PLOS GENETICS. 2012;8(5):e1002704
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Article: JOURNAL OF PROTEOME RESEARCH. 2011;10(12):5562-5567
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Article: PROTEOME SCIENCE. 2011;9:73
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Article: ANALYTICA CHIMICA ACTA. 2011;705(1-2):72-80
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Article: PLOS GENETICS. 2011;7(9):e1002270
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Article: MOLECULAR SYSTEMS BIOLOGY. 2011;7:525
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Article: PLOS ONE. 2011;6(11):e27338
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Article: FEMS MICROBIOLOGY ECOLOGY. 2010;73(3):577-586
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Article: JOURNAL OF PROTEOME RESEARCH. 2009;8(5):2361-2375
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Article: ANALYTICAL CHEMISTRY. 2009;81(6):2075-2084
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Article: BMC BIOINFORMATICS. 2008;9:106
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Article: BMC BIOINFORMATICS. 2008;9:105
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Article: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA. 2008;105(6):2117-2122
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Article: ANALYTICAL CHEMISTRY. 2007;79(15):5682-5689
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Article: JOURNAL OF CHEMOMETRICS. 2007;21(7-9):376-385
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Article: JOURNAL OF PROTEOME RESEARCH. 2006;5(10):2642-2655
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Article: JOURNAL OF CHEMOMETRICS. 2006;20(8-10):341-351
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Article: MOLECULAR BIOSYSTEMS. 2006;2(3-4):193-202
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Article: MOLECULAR BIOSYSTEMS. 2005;1(2):166-175
- Show more
All other publications
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Review: EUROPEAN UROLOGY FOCUS. 2021;7(4):687-691
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Review: JOURNAL OF INTERNAL MEDICINE. 2020;288(1):62-81
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Letter: JAMA ONCOLOGY. 2019;5(7):1060-1062
Employments
- Senior Lecturer, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 2020-
Degrees and Education
- Docent, Karolinska Institutet, 2020