CvS: Classification via Segmentation For Small Datasets

no code implementations • 29 Oct 2021 • Nooshin Mojab, Philip S. Yu, Joelle A. Hallak, Darvin Yi

The success of deep learning methods relies heavily on the availability of a large amount of data.

Classification

I-ODA, Real-World Multi-modal Longitudinal Data for OphthalmicApplications

no code implementations • 30 Mar 2021 • Nooshin Mojab, Vahid Noroozi, Abdullah Aleem, Manoj P. Nallabothula, Joseph Baker, Dimitri T. Azar, Mark Rosenblatt, RV Paul Chan, Darvin Yi, Philip S. Yu, Joelle A. Hallak

In this paper, we present a new multi-modal longitudinal ophthalmic imaging dataset, the Illinois Ophthalmic Database Atlas (I-ODA), with the goal of advancing state-of-the-art computer vision applications in ophthalmology, and improving upon the translatable capacity of AI based applications across different clinical settings.

Real-World Multi-Domain Data Applications for Generalizations to Clinical Settings

no code implementations • 24 Jul 2020 • Nooshin Mojab, Vahid Noroozi, Darvin Yi, Manoj Prabhakar Nallabothula, Abdullah Aleem, Phillip S. Yu, Joelle A. Hallak

However, real-world data is different and translations are yielding varying results.

Representation Learning Transfer Learning

Leveraging Semi-Supervised Learning for Fairness using Neural Networks

no code implementations • 31 Dec 2019 • Vahid Noroozi, Sara Bahaadini, Samira Sheikhi, Nooshin Mojab, Philip S. Yu

There has been a growing concern about the fairness of decision-making systems based on machine learning.

BIG-bench Machine Learning Decision Making +1