Author

Lara Rosaline Heij

Maastricht UniversityORCID 0000-0002-0602-3356Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 2 Organism:human· 2 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Assay:imaging· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Alexander T. PearsoniD· 2 shared Jakob Nikolas KatheriD· 2 shared Jefree J. SchulteiD· 2 shared Nicole A. CiprianiiD· 2 shared Sara E. KochannyiD· 2 shared Akash PatnaikiD· 1 shared Amelie EchleiD· 1 shared Andrew M. Hanby· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Alexander T. PearsonORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

The Impact of Digital Histopathology Batch Effect on Deep Learning Model Accuracy and Bias

Frederick Matthew Howard, James M. Dolezal, Sara E. Kochanny, Jefree J. Schulte, Heather Chen, Lara Rosaline Heij, Dezheng Huo, Rita Nanda, Olufunmilayo Ibironke Olopade, Jakob Nikolas Kather, Nicole A. Cipriani, Robert L. Grossman, Alexander T. Pearson

This paper shows that digital histopathology batch effects in TCGA data affect DL model accuracy and bias, and proposes a method to address this issue.

Nature Communications · Jul 20, 2021Peer-reviewedBioinformatics

Pan-cancer image-based detection of clinically actionable genetic alterations

Jakob Nikolas Kather, Lara Rosaline Heij, Heike Irmgard Grabsch, Chiara Maria Lavinia Loeffler, Amelie Echle, Hannah Sophie Muti, Jeremias Krause, Jan Niehues, Kai A. J. Sommer, Peter Bankhead, Loes F. S. Kooreman, Jefree J. Schulte, Nicole A. Cipriani, Roman David Buelow, Peter Boor, , Tom Luedde

This paper develops a deep learning method to predict genetic alterations from histological images across multiple cancer types.

Nature Cancer · Jul 27, 2020Peer-reviewedGenetics