The synergism of spatial metabolomics and morphometry improves machine learning‐based renal tumour subtype classification-Reference-Cited by-同舟云学术

The synergism of spatial metabolomics and morphometry improves machine learning‐based renal tumour subtype classification

Published:2022-02 Issue:2 Volume:12 Page:
ISSN:2001-1326
Container-title:Clinical and Translational Medicine
language:en
Short-container-title:Clinical & Translational Med

Author:

Prade Verena M.¹,Sun Na¹,Shen Jian¹,Feuchtinger Annette¹,Kunzke Thomas¹,Buck Achim¹,Schraml Peter²,Moch Holger²,Schwamborn Kristina³,Autenrieth Michael⁴,Gschwend Jürgen E.⁴,Erlmeier Franziska⁵⁶,Hartmann Arndt⁵⁶,Walch Axel¹^ORCID

Affiliation:

1. Research Unit Analytical Pathology Helmholtz Zentrum München – German Research Center for Environmental Health Neuherberg Germany

2. Institute of Pathology and Molecular Pathology University Hospital Zurich Zurich Switzerland

3. Institute of Pathology Technical University Munich Munich Germany

4. Department of Urology Technical University Munich Munich Germany

5. Institute of Pathology, University Hospital Erlangen Friedrich‐Alexander‐University Erlangen‐Nürnberg Erlangen Germany

6. Comprehensive Cancer Center Erlangen‐EMN (CCC ER‐EMN) Erlangen Germany

Funder

Deutsche Forschungsgemeinschaft

Publisher

Wiley

Subject