5 papers
A Multi-Agent System for Autonomous, Fine-Tuning-Free Clinical Symptom Detection: Development and Validation Study
Cameron Cagan, Pedram Fard, Jiazi Tian +3
Clinical notes contain many of the signs and symptoms that bring patients to care, yet this information rarely reaches structured fields. Existing extraction approaches either rely…
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…
Optimization Instability in Autonomous Agentic Workflows for Clinical Symptom Detection
Cameron Cagan, Pedram Fard, Jiazi Tian +3
Autonomous agentic workflows that iteratively refine their own behavior hold considerable promise, yet their failure modes remain poorly characterized. We investigate optimization…
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…
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…