49 citations · 117 across the 12 of their papers we have counts for
3 papers · 1 filter
Can-SAVE: Deploying Low-Cost and Population-Scale Cancer Screening via Survival Analysis Variables and EHR
Petr Philonenko, Vladimir Kokh, Pavel Blinov
Conventional medical cancer screening methods are costly, labor-intensive, and extremely difficult to scale. Although AI can improve cancer detection, most systems rely on complex…
Predicting COVID-19 and pneumonia complications from admission texts
Dmitriy Umerenkov, Oleg Cherkashin, Alexander Nesterov +4
In this paper we present a novel approach to risk assessment for patients hospitalized with pneumonia or COVID-19 based on their admission reports. We applied a Longformer neural n…
Whole-body PET image denoising for reduced acquisition time
Ivan Kruzhilov, Stepan Kudin, Luka Vetoshkin +2
This paper evaluates the performance of supervised and unsupervised deep learning models for denoising positron emission tomography (PET) images in the presence of reduced acquisit…