106 citations · 394 across the 16 of their papers we have counts for
17 papers
Robust Deep Learning for Myocardial Scar Segmentation in Cardiac MRI with Noisy Labels
Aida Moafi, Danial Moafi, Evgeny M. Mirkes +4
The accurate segmentation of myocardial scars from cardiac MRI is essential for clinical assessment and treatment planning. In this study, we propose a robust deep-learning pipelin…
Exploring the impact of social stress on the adaptive dynamics of COVID-19: Typing the behavior of naïve populations faced with epidemics
Innokentiy Kastalskiy, Andrei Zinovyev, Evgeny Mirkes +2
In the context of natural disasters, human responses inevitably intertwine with natural factors. The COVID-19 pandemic, as a significant stress factor, has brought to light profoun…
Learning from scarce information: using synthetic data to classify Roman fine ware pottery
Santos J. Núñez Jareño, Daniël P. van Helden, Evgeny M. Mirkes +2
In this article we consider a version of the challenging problem of learning from datasets whose size is too limited to allow generalisation beyond the training set. To address the…
Principal Components of the Meaning
Neslihan Suzen, Alexander Gorban, Jeremy Levesley +1
In this paper we argue that (lexical) meaning in science can be represented in a 13 dimension Meaning Space. This space is constructed using principal component analysis (singular…
Trajectories, bifurcations and pseudotime in large clinical datasets: applications to myocardial infarction and diabetes data
Sergey E. Golovenkin, Jonathan Bac, Alexander Chervov +5
Large observational clinical datasets become increasingly available for mining associations between various disease traits and administered therapy. These datasets can be considere…
Fractional norms and quasinorms do not help to overcome the curse of dimensionality
Evgeny M. Mirkes, Jeza Allohibi, Alexander N. Gorban
The curse of dimensionality causes the well-known and widely discussed problems for machine learning methods. There is a hypothesis that using of the Manhattan distance and even fr…