Nickolas Littlefield

According to our database, Nickolas Littlefield authored at least 9 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Uncertainty-Quantified and Explainable Age- and Sex-Aware Contrastive Learning for Knee Osteoarthritis Classification.

Fengyi Gao, Farnaz Rezvani, Yushui Han, Michael Kann, Nickolas Littlefield, Hilal Maradit Kremers, Adolph J. Yates, Johannes F. Plate, Ahmad P. Tafti

Proceedings of the 23rd IEEE International Symposium on Biomedical Imaging, 2026

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

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

Self-supervised Representation Learning for AI-Based Musculoskeletal Radiograph Registry Construction.

Nickolas Littlefield, Michael Kann, Monjurul Islam, Maimouna Sanogo, Zoe Menezes, Fengyi Gao, Nicole Myers, Samuel Ewalefo, MaCalus V. Hogan, Johannes F. Plate, Qiangqiang Gu, Ahmad P. Tafti

Proceedings of the Advances in Visual Computing - 20th International Symposium, 2025

Explainable Feature Engineering in Health Data Science: Empirical Comparison of ChatGPT-4o and Classical Machine Learning Methods.

Behshid Behkamal, Amin Rezaei, Nickolas Littlefield, Samarth Bhardwaj, Leah Reid, Nicole Myers, Soheyla Amirian, Ahmad P. Tafti

Proceedings of the ACM/IEEE International Conference on Connected Health: Applications, 2025

2024

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, Hooman H. Rashidi, Ahmad P. Tafti

J. Am. Medical Informatics Assoc., 2024

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

Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 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

Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

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, Hamidreza Moradi, Soheyla Amirian, Ahmad P. Tafti

Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2023