6 papers
Sequential Counterfactual Inference for Temporal Clinical Data: Addressing the Time Traveler Dilemma
Jingya Cheng, Alaleh Azhir, Jiazi Tian +1
Counterfactual inference enables clinicians to ask "what if" questions about patient outcomes, but standard methods assume feature independence and simultaneous modifiability -- as…
An N-of-1 Artificial Intelligence Ecosystem for Precision Medicine
Pedram Fard, Alaleh Azhir, Neguine Rezaii +2
Artificial intelligence in medicine is built to serve the average patient. By minimizing error across large datasets, most systems deliver strong aggregate accuracy yet falter at t…
A Hybrid Enumeration Framework for Optimal Counterfactual Generation in Post-Acute COVID-19 Heart Failure
Jingya Cheng, Alaleh Azhir, Jiazi Tian +1
Counterfactual inference provides a mathematical framework for reasoning about hypothetical outcomes under alternative interventions, bridging causal reasoning and predictive model…
TRIP: Coercion-resistant Registration for E-Voting with Verifiability and Usability in Votegral
Louis-Henri Merino, Simone Colombo, Rene Reyes +9
Online voting is convenient and flexible, but amplifies the risks of voter coercion and vote buying. One promising mitigation strategy enables voters to give a coercer fake voting…
The Average Patient Fallacy
Alaleh Azhir, Shawn N. Murphy, Hossein Estiri
Machine learning in medicine is typically optimized for population averages. This frequency weighted training privileges common presentations and marginalizes rare yet clinically c…
Signal Fidelity Index-Aware Calibration for Dementia Predictions Across Heterogeneous Real-World Data
Jingya Cheng, Jiazi Tian, Federica Spoto +3
\textbf{Background:} Machine learning models trained on electronic health records (EHRs) often degrade across healthcare systems due to distributional shift. A fundamental but unde…