4.2k citations · 4.8k across the 8 of their papers we have counts for
9 papers
Natural language processing to automatically extract the presence and severity of esophagitis in notes of patients undergoing radiotherapy
Shan Chen, Marco Guevara, Nicolas Ramirez +7
Radiotherapy (RT) toxicities can impair survival and quality-of-life, yet remain under-studied. Real-world evidence holds potential to improve our understanding of toxicities, but…
What Does DALL-E 2 Know About Radiology?
Lisa C. Adams, Felix Busch, Daniel Truhn +3
Generative models such as DALL-E 2 could represent a promising future tool for image generation, augmentation, and manipulation for artificial intelligence research in radiology pr…
Deep Learning-based Assessment of Hepatic Steatosis on chest CT
Zhongyi Zhang, Jakob Weiss, Jana Taron +3
Purpose: Automatic methods are required for the early detection of hepatic steatosis to avoid progression to cirrhosis and cancer. Here, we developed a fully automated deep learnin…
Deep learning-based detection of intravenous contrast in computed tomography scans
Zezhong Ye, Jack M. Qian, Ahmed Hosny +7
Purpose: Identifying intravenous (IV) contrast use within CT scans is a key component of data curation for model development and testing. Currently, IV contrast is poorly documente…
The importance of transparency and reproducibility in artificial intelligence research
Benjamin Haibe-Kains, George Alexandru Adam, Ahmed Hosny +17
In their study, McKinney et al. showed the high potential of artificial intelligence for breast cancer screening. However, the lack of detailed methods and computer code undermines…
ModelHub.AI: Dissemination Platform for Deep Learning Models
Ahmed Hosny, Michael Schwier, Christoph Berger +13
Recent advances in artificial intelligence research have led to a profusion of studies that apply deep learning to problems in image analysis and natural language processing among…
Repeatability of Multiparametric Prostate MRI Radiomics Features
Michael Schwier, Joost van Griethuysen, Mark G Vangel +7
In this study we assessed the repeatability of the values of radiomics features for small prostate tumors using test-retest Multiparametric Magnetic Resonance Imaging (mpMRI) image…
Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer
Martin Vallières, Emily Kay-Rivest, Léo Jean Perrin +9
Quantitative extraction of high-dimensional mineable data from medical images is a process known as radiomics. Radiomics is foreseen as an essential prognostic tool for cancer risk…
Image biomarker standardisation initiative
Alex Zwanenburg, Stefan Leger, Martin Vallières +1
The image biomarker standardisation initiative (IBSI) is an independent international collaboration which works towards standardising the extraction of image biomarkers from acquir…