1 citations · 1 across the 5 of their papers we have counts for
6 papers
Imputation-free transformer learning enables robust Alzheimer's disease prediction and calibrated uncertainty quantification across heterogeneous clinical cohorts
Christelle Schneuwly Diaz, Narmina Baghirova, Duy-Thanh Vu +4
Accurate diagnostic classification and disease-severity prediction for Alzheimer's disease are hampered by the incompleteness and heterogeneity of real-world clinical data. Left un…
Perfect phylogenies via the Minimum Uncovering Branching problem: efficiently solvable cases
Narmina Baghirova, Esther Galby, Martin Milanič
In this paper, we present new efficiently solvable cases of the Minimum Uncovering Branching problem, an optimization problem with applications in cancer genomics introduced by Huj…
Explainable Graph-theoretical Machine Learning with Application to Alzheimer's Disease Prediction
Narmina Baghirova, Duy-Thanh Vũ, Duy-Cat Can +6
Dementia affects over 55 million people worldwide, projected to reach 139 million by 2050, with Alzheimer's disease (AD) accounting for 60-70% of cases. AD is associated with disru…
Proportionally dense subgraphs of maximum size in degree-constrained graphs
Narmina Baghirova, Antoine Castillon
A proportionally dense subgraph (PDS) of a graph is an induced subgraph of size at least two such that every vertex in the subgraph has proportionally as many neighbors inside as o…
Finding -community structures in special graph classes
Narmina Baghirova, Clément Dallard, Bernard Ries +1
For a fixed integer , a -community structure in an undirected graph is a partition of its vertex set into sets called communities, each of size at least two, such th…
Locally checkable problems parameterized by clique-width
Narmina Baghirova, Carolina Lucía Gonzalez, Bernard Ries +1
We continue the study initiated by Bonomo-Braberman and Gonzalez in 2020 on -locally checkable problems. We propose a dynamic programming algorithm that takes as input a graph w…