Connecting Histopathology Imaging and Proteomics in Kidney Cancer through Machine Learning
Proteomics data encode molecular features of diagnostic value and accurately reflect key underlying biological mechanisms in cancers. Histopathology imaging is a well-established clinical approach to cancer diagnosis. The predictive relationship between large-scale proteomics and H&E-stained...
Main Authors: | Francisco Azuaje, Sang-Yoon Kim, Daniel Perez Hernandez, Gunnar Dittmar |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-09-01
|
Series: | Journal of Clinical Medicine |
Subjects: | |
Online Access: | https://www.mdpi.com/2077-0383/8/10/1535 |
Similar Items
-
Histomorphological Spectrum of Nephrectomy Specimens- A Tertairy Care Centre Experience
by: Vikram Narang, et al.
Published: (2016-04-01) -
Histological Tracking into the Third Dimension: Evolution of Early Tumorigenesis in VHL Kidney
by: Mayyan Mubarak, et al.
Published: (2021-09-01) -
Collision Tumour of the Kidney: A Case Report
by: V Marisa D Souza, et al.
Published: (2021-01-01) -
Identification of a Novel Protein-Based Signature to Improve Prognosis Prediction in Renal Clear Cell Carcinoma
by: Guangdi Chu, et al.
Published: (2021-03-01) -
Molecular and Metabolic Subtypes in Sporadic and Inherited Clear Cell Renal Cell Carcinoma
by: Maria F. Czyzyk-Krzeska, et al.
Published: (2021-03-01)