ProfessorsProfessors of University of North Carolina at CharlotteMirsad Hadzikadic

Mirsad Hadzikadic

University of North Carolina at Charlotte

H-index: 19

North America-United States

About Mirsad Hadzikadic

Mirsad Hadzikadic, With an exceptional h-index of 19 and a recent h-index of 15 (since 2020), a distinguished researcher at University of North Carolina at Charlotte, specializes in the field of complex systems, data mining, health informatics, cognitive science, public policy.

His recent articles reflect a diverse array of research interests and contributions to the field:

Combating propaganda texts using transfer learning

The Influence of Decorations and Word Appearances on the Relative Size Judgment in Viewers of Tag Clouds

Modeling Genocide: An Agent-Based Model of Bystander Motivations and Societal Restraints

Predicting neural deterioration in patients with alzheimer’s disease using a convolutional neural network

Mirsad Hadzikadic Information

University	University of North Carolina at Charlotte
Position	Professor
Citations(all)	1197
Citations(since 2020)	719
Cited By	712
hIndex(all)	19
hIndex(since 2020)	15
i10Index(all)	36
i10Index(since 2020)	22
Email	Access Email
University Profile Page	University of North Carolina at Charlotte
Google Scholar	View Google Scholar Profile

Mirsad Hadzikadic Skills & Research Interests

complex systems

data mining

health informatics

cognitive science

public policy

Top articles of Mirsad Hadzikadic

Title	Journal	Author(s)	Publication Date
Combating propaganda texts using transfer learning	Int J Artif Intell ISSN	Malak Abdullah Dia Abujaber Ahmed Al-Qarqaz Rob Abbott Mirsad Hadzikadic	2023/6/1
The Influence of Decorations and Word Appearances on the Relative Size Judgment in Viewers of Tag Clouds		Khaldoon Dhou Robert Kosara Mirsad Hadzikadic Mark Faust	2021
Modeling Genocide: An Agent-Based Model of Bystander Motivations and Societal Restraints		Elizabeth von Briesen Amy Canevello Samira Shaikh John Cox Mirsad Hadžikadić	2021
Predicting neural deterioration in patients with alzheimer’s disease using a convolutional neural network		H Maryam Tavakoli Tianyi Xie Jingyi Shi Mirsad Hadzikadic Yaorong Ge	2020/12/16