4 citations · 6 across the 2 of their papers we have counts for
3 papers
cs.LG2022★ 4 cited
The Need for Interpretable Features: Motivation and Taxonomy
Alexandra Zytek, Ignacio Arnaldo, Dongyu Liu +2
Through extensive experience developing and explaining machine learning (ML) applications for real-world domains, we have learned that ML models are only as interpretable as their…
cs.HC2021★ 2 cited
VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models
Furui Cheng, Dongyu Liu, Fan Du +5
Machine learning (ML) is increasingly applied to Electronic Health Records (EHRs) to solve clinical prediction tasks. Although many ML models perform promisingly, issues with model…
cs.HC2021
Sibyl: Understanding and Addressing the Usability Challenges of Machine Learning In High-Stakes Decision Making
Alexandra Zytek, Dongyu Liu, Rhema Vaithianathan +1
Machine learning (ML) is being applied to a diverse and ever-growing set of domains. In many cases, domain experts - who often have no expertise in ML or data science - are asked t…