activity
20162025
most citedSimiNet: a Novel Method for Quantifying Brain Network Similarity

45 citations · 57 across the 9 of their papers we have counts for

collaborators
Showing q-bio.NCShow all

6 papers · 1 filter

q-bio.NC2021

An Electroencephalography connectome predictive model of major depressive disorder severity

Aya Kabbara, Gabriel Robert, Mohamad Khalil +3

Emerging evidence showed that major depressive disorder (MDD) is associated with disruptions of brain structural and functional networks, rather than impairment of isolated brain r…

q-bio.NC2017★ 45 cited

SimiNet: a Novel Method for Quantifying Brain Network Similarity

Ahmad Mheich, Mahmoud Hassan, Mohamad Khalil +3

Quantifying the similarity between two networks is critical in many applications. A number of algorithms have been proposed to compute graph similarity, mainly based on the propert…

q-bio.NC2017

A scalp-EEG network-based analysis of Alzheimer's disease patients at rest

Aya Kabbara, Mahmoud Hassan, Mohamad Khalil +2

Most brain disorders including Alzheimer's disease (AD) are related to alterations in the normal brain network organization and function. Exploring these network alterations using…

q-bio.NC2016★ 3 cited

Graph analysis of spontaneous brain network using EEG source connectivity

Aya Kabbara, Wassim El Falou, Mohamad Khalil +2

Exploring the human brain networks during rest is a topic of great interest. Several structural and functional studies have previously been conducted to study the intrinsic brain n…

q-bio.NC2016★ 1 cited

Combining EEG source connectivity and network similarity: Application to object categorization in the human brain

Ahmad Mheich, Mahmoud Hassan, Olivier Dufor +2

A major challenge in cognitive neuroscience is to evaluate the ability of the human brain to categorize or group visual stimuli based on common features. This categorization proces…

q-bio.NC2016★ 3 cited

A node-wise analysis of the uterine muscle networks for pregnancy monitoring

N. Nader, M. Hassan, W. Falou +2

The recent past years have seen a noticeable increase of interest in the correlation analysis of electrohysterographic (EHG) signals in the perspective of improving the pregnancy m…