◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

I. Skampardoni

3 papers hereh-index 10442 citations23 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG3

identity via Semantic Scholar / OpenAlex

most citedApplications of Generative Adversarial Networks in Neuroimaging and Clinical Neuroscience

106 citations · 139 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2024★ 33 cited

A comprehensive interpretable machine learning framework for Mild Cognitive Impairment and Alzheimer's disease diagnosis

Maria Eleftheria Vlontzou, Maria Athanasiou, Kalliopi Dalakleidi +3

An interpretable machine learning (ML) framework is introduced to enhance the diagnosis of Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) by ensuring robustness of th…

cs.LG2024

Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning

Junhao Wen, Mathilde Antoniades, Zhijian Yang +4

Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in neuropsychiatric and neu…

cs.LG2022★ 106 cited

Applications of Generative Adversarial Networks in Neuroimaging and Clinical Neuroscience

Rongguang Wang, Vishnu Bashyam, Zhijian Yang +10

Generative adversarial networks (GANs) are one powerful type of deep learning models that have been successfully utilized in numerous fields. They belong to a broader family called…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.