Open AccessThe synergism of spatial metabolomics and morphometry improves machine learning‐based renal tumour subtype classification
Author(s) -
Prade Verena M.,
Sun Na,
Shen Jian,
Feuchtinger Annette,
Kunzke Thomas,
Buck Achim,
Schraml Peter,
Moch Holger,
Schwamborn Kristina,
Autenrieth Michael,
Gschwend Jürgen E.,
Erlmeier Franziska,
Hartmann Arndt,
Walch Axel
Publication year - 2022
Publication title -
clinical and translational medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.125
H-Index - 1
ISSN - 2001-1326
DOI - 10.1002/ctm2.666
Subject(s) - subtyping , chromophobe cell , clear cell , renal cell carcinoma , biomarker discovery , pathology , metabolomics , mass spectrometry imaging , biomarker , medicine , immunohistochemistry , clear cell renal cell carcinoma , kidney cancer , computational biology , oncology , proteomics , bioinformatics , biology , mass spectrometry , computer science , chemistry , biochemistry , chromatography , gene , programming language