8 citations · 22 across the 16 of their papers we have counts for
7 papers · 1 filter
FairSelect: A Systematic Evaluation of Multi-Level and Intersectional Algorithmic Fairness
Nick Souligne, Isabella Mixton-Garcia, Vignesh Subbian
Algorithmic fairness methods are increasingly used to identify and mitigate bias in machine learning models, yet most approaches are evaluated in isolation and along single demogra…
FairLogue: A Toolkit for Intersectional Fairness Analysis in Clinical Machine Learning Models
Nick Souligne, Vignesh Subbian
Objective: Algorithmic fairness is essential for equitable and trustworthy machine learning in healthcare. Most fairness tools emphasize single-axis demographic comparisons and may…
Failure Modes of Time Series Interpretability Algorithms for Critical Care Applications and Potential Solutions
Shashank Yadav, Vignesh Subbian
Interpretability plays a vital role in aligning and deploying deep learning models in critical care, especially in constantly evolving conditions that influence patient survival. H…
Discovery of Generalizable TBI Phenotypes Using Multivariate Time-Series Clustering
Hamid Ghaderi, Brandon Foreman, Chandan K. Reddy +1
Traumatic Brain Injury (TBI) presents a broad spectrum of clinical presentations and outcomes due to its inherent heterogeneity, leading to diverse recovery trajectories and varied…
Identifying TBI Physiological States by Clustering Multivariate Clinical Time-Series Data
Hamid Ghaderi, Brandon Foreman, Amin Nayebi +3
Determining clinically relevant physiological states from multivariate time series data with missing values is essential for providing appropriate treatment for acute conditions su…
A Self-Supervised Learning-based Approach to Clustering Multivariate Time-Series Data with Missing Values (SLAC-Time): An Application to TBI Phenotyping
Hamid Ghaderi, Brandon Foreman, Amin Nayebi +3
Self-supervised learning approaches provide a promising direction for clustering multivariate time-series data. However, real-world time-series data often include missing values, a…
WindowSHAP: An Efficient Framework for Explaining Time-series Classifiers based on Shapley Values
Amin Nayebi, Sindhu Tipirneni, Chandan K Reddy +2
Unpacking and comprehending how black-box machine learning algorithms make decisions has been a persistent challenge for researchers and end-users. Explaining time-series predictiv…