John N. Aucott

According to our database, John N. Aucott authored at least 7 papers between 2018 and 2024.

Collaborative distances:

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

2024

PFEDEDIT: Personalized Federated Learning via Automated Model Editing.

Haolin Yuan, William Paul, John N. Aucott, Philippe Burlina, Yinzhi Cao

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

EdgeMixup: Embarrassingly Simple Data Alteration to Improve Lyme Disease Lesion Segmentation and Diagnosis Fairness.

Haolin Yuan, John N. Aucott, Armin Hadzic, William Paul, Marcia Villegas de Flores, Philip Mathew, Philippe Burlina, Yinzhi Cao

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

2022

EdgeMixup: Improving Fairness for Skin Disease Classification and Segmentation.

Haolin Yuan, Armin Hadzic, William Paul, Daniella Villegas de Flores, Philip Mathew, John N. Aucott, Yinzhi Cao, Philippe Burlina

CoRR, 2022

2020

AI Progress in Skin Lesion Analysis.

Philippe M. Burlina, William Paul, Phil A. Mathew, Neil J. Joshi, Alison W. Rebman, John N. Aucott

CoRR, 2020

AI-based detection of erythema migrans and disambiguation against other skin lesions.

Philippe M. Burlina, Neil J. Joshi, Phil A. Mathew, William Paul, Alison W. Rebman, John N. Aucott

Comput. Biol. Medicine, 2020

2019

Automated detection of erythema migrans and other confounding skin lesions via deep learning.

Philippe M. Burlina, Neil Joshi, Elise Ng, Seth D. Billings, Alison W. Rebman, John N. Aucott

Comput. Biol. Medicine, 2019

2018

Skin Image Analysis for Erythema Migrans Detection and Automated Lyme Disease Referral.

Philippe Burlina, Neil Joshi, Elise Ng, Seth Billings, Alison W. Rebman, John N. Aucott

Proceedings of the OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, - and - Skin Image Analysis, 2018