Automatic Image and Video Caption Generation With Deep Learning: A Concise Review and Algorithmic Overlap. - Soheyla Amirian; Khaled Rasheed; Thiab R. Taha; Hamid R. Arabnia (IEEE Access, 2020)

Stereotype-Free Classification of Fictitious Faces. - Mohammadhossein Toutiaee; Soheyla Amirian; John A. Miller 001; Sheng Li 001 (CoRR, 2020)

Generative Adversarial Network Applications in Creating a Meta-Universe. - Soheyla Amirian; Thiab R. Taha; Khaled Rasheed; Hamid R. Arabnia (CSCI, 2021)

The Use of Video Captioning for Fostering Physical Activity. - Soheyla Amirian; Abolfazl Farahani; Hamid R. Arabnia; Khaled Rasheed; Thiab R. Taha (CoRR, 2021)

Automatic Generation of Descriptive Titles for Video Clips Using Deep Learning. - Soheyla Amirian; Khaled Rasheed; Thiab R. Taha; Hamid R. Arabnia (CoRR, 2021)

Word Embedding Neural Networks to Advance Knee Osteoarthritis Research. - Soheyla Amirian; Husam Ghazaleh; Mehdi Assefi; Hilal Maradit Kremers; Hamid R. Arabnia; Johannes F. Plate; Ahmad P. Tafti (CSCI, 2022)

An Integrated Approach for Video Captioning and Applications. - Soheyla Amirian; Thiab R. Taha; Khaled Rasheed; Hamid R. Arabnia (CoRR, 2022)

Learning Unbiased Image Segmentation: A Case Study with Plain Knee Radiographs. - Nickolas Littlefield; Johannes F. Plate; Kurt R. Weiss; Ines Lohse; Avani Chhabra; Ismaeel A. Siddiqui; Zoe Menezes; George M. Mastorakos; Sakshi Mehul Thakar; Mehrnaz Abedian; Matthew F. Gong; Luke A. Carlson; et al. (BHI, 2023)

Enforcing Explainable Deep Few-Shot Learning to Analyze Plain Knee Radiographs: Data from the Osteoarthritis Initiative. - Nickolas Littlefield; Hamidreza Moradi; Soheyla Amirian; Hilal Maradit Kremers; Johannes F. Plate; Ahmad P. Tafti (ICHI, 2023)

AI Fairness in Hip Bony Anatomy Segmentation: Analyzing and Mitigating Gender and Racial Bias in Plain Radiography Analysis. - Nickolas Littlefield; Johannes F. Plate; Kurt R. Weiss; Ines Lohse; Avani Chhabra; Ismaeel A. Siddiqui; Zoe Menezes; George M. Mastorakos; Soheyla Amirian; Hamidreza Moradi; Ahmad P. Tafti (ICHI, 2023)

Explainable AI in Orthopedics: Challenges, Opportunities, and Prospects. - Soheyla Amirian; Luke A. Carlson; Matthew F. Gong; Ines Lohse; Kurt R. Weiss; Johannes F. Plate; Ahmad P. Tafti (CoRR, 2023)

Generative AI in orthopedics: an explainable deep few-shot image augmentation pipeline for plain knee radiographs and Kellgren-Lawrence grading. - Nickolas Littlefield; Soheyla Amirian; Jacob T. Biehl; Edward G. Andrews; Michael Kann; Nicole Myers; Leah Reid; Adolph J. Yates; Brian J. McGrory; Bambang Parmanto; Thorsten M. Seyler; Johannes F. Plate; et al. (J. Am. Medical Informatics Assoc., 2024)

State-of-the-Art in Responsible, Explainable, and Fair AI for Medical Image Analysis. - Soheyla Amirian; Fengyi Gao; Nickolas Littlefield; Jonathan H. Hill; Adolph J. Yates; Johannes F. Plate; Liron Pantanowitz; Hooman H. Rashidi; Ahmad P. Tafti (IEEE Access, 2025)

Predicting cancer survival at different stages: Insights from fair and explainable machine learning approaches. - Tejasvi Sanjay Kamble; Hongtao Wang; Nicole Myers; Nickolas Littlefield; Leah Reid; Cynthia S. McCarthy; Young Ji Lee; Hongfang Liu; Liron Pantanowitz; Soheyla Amirian; Hooman H. Rashidi; Ahmad P. Tafti (Int. J. Medical Informatics, 2025)