This is

Computational and
Translational pathology

Backed by cutting-edge machine learning algorithms, the mission of CTP laboratory is to help doctors make precise diagnostic and prognostic decisions for the well-being of patients.

Our Research

artificial intelligence, brain, think
dna, abstract, blood
stem, cells, embryonic
bacteria, illness, virus

Digital Dignostics

Morpho-Molecular pathology

tumor Immunology

tumor profiler

Causal inference

Our Publication

Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), histological grading is a poor predictor of disease progression, and consensus molecular subtypes (CMSs) cannot be distinguished without gene expression profiling. We hypothesise that image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data and to resolve unclassifiable or heterogeneous cases. In this study, we present an image-based approach to predict CRC CMS from standard H&E sections using deep learning.

References:

imCMS: The door to simple, cheap, reliable bio-stratification. Mark Nicholls, 07.05.2020

Researchers use artificial intelligence to establish molecular tumor classification and prognosis in patients with colorectal cancer, 04.07.2019

Researchers use artificial intelligence to help tailor bowel cancer treatment. 2019 

 

 
 
OUR TEAM

Clinical Experts

Well-trained in pathology

Data Analysts

Proficient in big-data

AI Researchers

Insightful in AI algorithm

Our Vision