Area of research
Artificial Intelligence · Radiology, Nuclear Medicine and Imaging
Research interest
Research focused on Artificial intelligence and Deep learning, with related work in Histology, Cancer, Gompertz function. Notable publications include 'Pan-cancer image-based detection of clinically actionable genetic alterations', 'Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology', and 'Classical mathematical models for prediction of response to chemotherapy and immunotherapy'.
HIBRID: histology-based risk-stratification with deep learning and ctDNA in colorectal cancer
Assessing genotype−phenotype correlations in colorectal cancer with deep learning: a multicentre cohort study
End-to-end deep learning versus machine learning for biomarker discovery in cancer genomes
Regression-based Deep-Learning predicts molecular biomarkers from pathology slides
Deep learning for dual detection of microsatellite instability and POLE mutations in colorectal cancer histopathology
Automated curation of large‐scale cancer histopathology image datasets using deep learning
An overview and a roadmap for artificial intelligence in hematology and oncology
Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology
Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology
Classical mathematical models for prediction of response to chemotherapy and immunotherapy
Erratum to ‘Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology’ Medical Image Analysis, Volume 79, July 2022, 102474
Artificial Intelligence–based Detection of FGFR3 Mutational Status Directly from Routine Histology in Bladder Cancer: A Possible Preselection for Molecular Testing?
Benchmarking artificial intelligence methods for end-to-end computational pathology
Pan-cancer image-based detection of clinically actionable genetic alterations
The Aachen Protocol for Deep Learning Histopathology: A hands-on guide for data preprocessing
Author Correction: Pan-cancer image-based detection of clinically actionable genetic alterations
Pan-cancer image-based detection of clinically actionable genetic alterations
Deep learning detects virus presence in cancer histology