18 citations · 21 across the 5 of their papers we have counts for
5 papers
FOCAL: A Cost-Aware Video Dataset for Active Learning
Kiran Kokilepersaud, Yash-Yee Logan, Ryan Benkert +6
In this paper, we introduce the FOCAL (Ford-OLIVES Collaboration on Active Learning) dataset which enables the study of the impact of annotation-cost within a video active learning…
OLIVES Dataset: Ophthalmic Labels for Investigating Visual Eye Semantics
Mohit Prabhushankar, Kiran Kokilepersaud, Yash-yee Logan +3
Clinical diagnosis of the eye is performed over multifarious data modalities including scalar clinical labels, vectorized biomarkers, two-dimensional fundus images, and three-dimen…
Patient Aware Active Learning for Fine-Grained OCT Classification
Yash-yee Logan, Ryan Benkert, Ahmad Mustafa +2
This paper considers making active learning more sensible from a medical perspective. In practice, a disease manifests itself in different forms across patient cohorts. Existing fr…
DECAL: DEployable Clinical Active Learning
Yash-yee Logan, Mohit Prabhushankar, Ghassan AlRegib
Conventional machine learning systems that operate on natural images assume the presence of attributes within the images that lead to some decision. However, decisions in medical d…
Multi-Modal Learning Using Physicians Diagnostics for Optical Coherence Tomography Classification
Y. Logan, K. Kokilepersaud, G. Kwon +3
In this paper, we propose a framework that incorporates experts diagnostics and insights into the analysis of Optical Coherence Tomography (OCT) using multi-modal learning. To demo…