K-OPLS package: Kernel-based orthogonal projections to latent structures for prediction and interpretation in feature space. - Max Bylesjö; Mattias Rantalainen; Jeremy K. Nicholson; Elaine Holmes; Johan Trygg (BMC Bioinform., 2008)

Piecewise multivariate modelling of sequential metabolic profiling data. - Mattias Rantalainen; Olivier Cloarec; Timothy M. D. Ebbels; Torbjörn Lundstedt; Jeremy K. Nicholson; Elaine Holmes; Johan Trygg (BMC Bioinform., 2008)

Beta-Poisson model for single-cell RNA-seq data analyses. - Trung-Nghia Vu; Quin F. Wills; Krishna R. Kalari; Nifang Niu; Liewei Wang; Mattias Rantalainen; Yudi Pawitan (Bioinform., 2016)

E-Science technologies in a workflow for personalized medicine using cancer screening as a case study. - Ola Spjuth; Andreas Karlsson; Mark Clements; Keith Humphreys; Emma Ivansson; Jim Dowling; Martin Eklund; Alexandra Jauhiainen; Kamila Czene; Henrik Gronberg; Pär Sparén; Fredrik Wiklund; et al. (J. Am. Medical Informatics Assoc., 2017)

Isoform-level gene expression patterns in single-cell RNA-sequencing data. - Trung-Nghia Vu; Quin F. Wills; Krishna R. Kalari; Nifang Niu; Liewei Wang; Yudi Pawitan; Mattias Rantalainen (Bioinform., 2018)

Pathologist-Level Grading of Prostate Biopsies with Artificial Intelligence. - Peter Ström; Kimmo Kartasalo; Henrik Olsson; Leslie Solorzano; Brett Delahunt; Daniel M. Berney; David G. Bostwick; Andrew J. Evans; David J. Grignon; Peter A. Humphrey; Kenneth A. Iczkowski; James G. Kench; et al. (CoRR, 2019)

Predicting molecular phenotypes from histopathology images: a transcriptome-wide expression-morphology analysis in breast cancer. - Yinxi Wang; Kimmo Kartasalo; Masi Valkonen; Christer Larsson; Pekka Ruusuvuori; Johan Hartman; Mattias Rantalainen (CoRR, 2020)

An investigation of attention mechanisms in histopathology whole-slide-image analysis for regression objectives. - Philippe Weitz; Yinxi Wang; Johan Hartman; Mattias Rantalainen (ICCVW, 2021)

Using deep learning to detect patients at risk for prostate cancer despite benign biopsies. - Bojing Liu; Yinxi Wang; Philippe Weitz; Johan Lindberg; Lars Egevad; Henrik Grönberg; Martin Eklund; Mattias Rantalainen (CoRR, 2021)

Transcriptome-wide prediction of prostate cancer gene expression from histopathology images using co-expression-based convolutional neural networks. - Philippe Weitz; Yinxi Wang; Kimmo Kartasalo; Lars Egevad; Johan Lindberg; Henrik Grönberg; Martin Eklund; Mattias Rantalainen (Bioinform., 2022)

ACROBAT - a multi-stain breast cancer histological whole-slide-image data set from routine diagnostics for computational pathology. - Philippe Weitz; Masi Valkonen; Leslie Solorzano; Circe Carr; Kimmo Kartasalo; Constance Boissin; Sonja Koivukoski; Aino Kuusela; Dusan Rasic; Yanbo Feng; Sandra Kristiane Sinius Pouplier; Abhinav Sharma; et al. (CoRR, 2022)

Increasing the usefulness of already existing annotations through WSI registration. - Philippe Weitz; Viktoria Sartor; Balazs Acs; Stephanie Robertson; Daniel Budelmann; Johan Hartman; Mattias Rantalainen (CoRR, 2023)

Physical Color Calibration of Digital Pathology Scanners for Robust Artificial Intelligence Assisted Cancer Diagnosis. - Xiaoyi Ji; Richard Salmon; Nita Mulliqi; Umair Khan; Yinxi Wang; Anders Blilie; Henrik Olsson; Bodil Ginnerup Pedersen; Karina Dalsgaard Sørensen; Benedicte Parm Ulhøi; Svein Reidar Kjosavik; Emilius A. M. Janssen; et al. (CoRR, 2023)

WEEP: A method for spatial interpretation of weakly supervised CNN models in computational pathology. - Abhinav Sharma; Bojing Liu; Mattias Rantalainen (CoRR, 2024)

Deep Blur Multi-Model (DeepBlurMM) - a strategy to mitigate the impact of image blur on deep learning model performance in histopathology image analysis. - Yujie Xiang; Bojing Liu; Mattias Rantalainen (CoRR, 2024)

Evaluating Deep Regression Models for WSI-Based Gene-Expression Prediction. - Fredrik K. Gustafsson; Mattias Rantalainen (CoRR, 2024)

Evaluating Computational Pathology Foundation Models for Prostate Cancer Grading under Distribution Shifts. - Fredrik K. Gustafsson; Mattias Rantalainen (CoRR, 2024)

The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue. - Philippe Weitz; Masi Valkonen; Leslie Solorzano; Circe Carr; Kimmo Kartasalo; Constance Boissin; Sonja Koivukoski; Aino Kuusela; Dusan Rasic; Yanbo Feng; Sandra Kristiane Sinius Pouplier; Abhinav Sharma; et al. (Medical Image Anal., 2024)