State-of-the-Art Periorbital Distance Prediction and Disease Classification Using Periorbital Features. - George R. Nahass; Ghasem Yazdanpanah; Madison Cheung; Alex Palacios; Jeffery Peterson; Kevin Heinze; Sasha Hubschman; Chad A. Purnell; Pete Setabutr; Ann Q. Tran; Darvin Yi (CoRR, 2024)

Open-Source Periorbital Segmentation Dataset for Ophthalmic Applications. - George R. Nahass; Emma Koehler; Nicholas Tomaras; Danny Lopez; Madison Cheung; Alexander Palacios; Jeffery Peterson; Sasha Hubschman; Kelsey Green; Chad A. Purnell; Pete Setabutr; Ann Q. Tran; et al. (CoRR, 2024)

Trends, Challenges, and Future Directions in Deep Learning for Glaucoma: A Systematic Review. - Mahtab Faraji; Homa Rashidisabet; George R. Nahass; RV Paul Chan; Thasarat S. Vajaranant; Darvin Yi (CoRR, 2024)

Normscan: open-source Python software to create average models from CT scans. - George R. Nahass; Mitchell A. Marques; Naji Bou Zeid; Linping Zhao; Lee W. T. Alkureishi (Int. J. Comput. Assist. Radiol. Surg., 2025)

Prediction of Lung Metastasis from Hepatocellular Carcinoma using the SEER Database. - Jeff J. H. Kim; George R. Nahass; Yang Dai; Theja Tulabandhula (CoRR, 2025)

Mathematical methods for assessing the accuracy of pre-planned and guided surgical osteotomies. - George R. Nahass; Nicolas Kaplan; Isabel Scharf; Devansh Saini; Naji Bou Zeid; Sobhi Kazmouz; Linping Zhao; Lee W. T. Alkureishi (Int. J. Comput. Assist. Radiol. Surg., 2025)

Targeted Unlearning Using Perturbed Sign Gradient Methods With Applications On Medical Images. - George R. Nahass; Zhu Wang; Homa Rashidisabet; Won Hwa Kim; Sasha Hubschman; Jeffrey C. Peterson; Ghasem Yazdanpanah; Chad A. Purnell; Pete Setabutr; Ann Q. Tran; Darvin Yi; Sathya N. Ravi (CoRR, 2025)

AI Anxiety: a comprehensive analysis of psychological factors and interventions. - Jeff J. H. Kim; Junyoung Soh; Shrinidhi Kadkol; Itay Solomon; Hyelin Yeh; Adith V. Srivatsa; George R. Nahass; Jeong Yun Choi; Sophie Lee; Theresa Nyugen; Olusola Ajilore (AI Ethics, 2025)