64 citations · 96 across the 6 of their papers we have counts for
9 papers
Downstream Fairness Caveats with Synthetic Healthcare Data
Karan Bhanot, Ioana Baldini, Dennis Wei +2
This paper evaluates synthetically generated healthcare data for biases and investigates the effect of fairness mitigation techniques on utility-fairness. Privacy laws limit access…
Biomedical Interpretable Entity Representations
Diego Garcia-Olano, Yasumasa Onoe, Ioana Baldini +3
Pre-trained language models induce dense entity representations that offer strong performance on entity-centric NLP tasks, but such representations are not immediately interpretabl…
Automated Meta-Analysis: A Causal Learning Perspective
Lu Cheng, Dmitriy A. Katz-Rogozhnikov, Kush R. Varshney +1
Meta-analysis is a systematic approach for understanding a phenomenon by analyzing the results of many previously published experimental studies. It is central to deriving conclusi…
Drug Repurposing for Cancer: An NLP Approach to Identify Low-Cost Therapies
Shivashankar Subramanian, Ioana Baldini, Sushma Ravichandran +7
More than 200 generic drugs approved by the U.S. Food and Drug Administration for non-cancer indications have shown promise for treating cancer. Due to their long history of safe p…
How Data Scientists Work Together With Domain Experts in Scientific Collaborations: To Find The Right Answer Or To Ask The Right Question?
Yaoli Mao, Dakuo Wang, Michael Muller +4
In recent years there has been an increasing trend in which data scientists and domain experts work together to tackle complex scientific questions. However, such collaborations of…
Teaching machines to understand data science code by semantic enrichment of dataflow graphs
Evan Patterson, Ioana Baldini, Aleksandra Mojsilovic +1
Your computer is continuously executing programs, but does it really understand them? Not in any meaningful sense. That burden falls upon human knowledge workers, who are increasin…