5 papers
Estimating Treatment Effects for Depression in Longitudinal Therapy Switching Settings
Xinyu Qin, Martin Katzman, Alexandria Greifenberger +5
Depression treatment often requires switching medications due to inadequate response or adverse effects. Estimating individualized treatment effects in this setting is challenging…
Can Physician Expertise Improve Machine Learning Identification of Delirium?
Xinyu Qin, Vicky Ye, Ruiheng Yu +1
Delirium is common in hospitalized patients and is often missed in routine care. We present a user-centered interactive machine learning (UC-iML) framework for delirium detection s…
Treatment Response Optimized Clinical Decision Support AI System via Digital Twin Simulation
Xinyu Qin, Anil K. Sood, Ruiheng Yu +3
Clinical decision support AI systems (CDSASs) must adapt to evolving patient conditions in real-time while adhering to strict safety constraints. We present an online adaptive fram…
Reinforcement Learning enhanced Online Adaptive Clinical Decision Support via Digital Twin powered Policy and Treatment Effect optimized Reward
Xinyu Qin, Ruiheng Yu, Lu Wang
Clinical decision support must adapt online under safety constraints. We present an online adaptive tool where reinforcement learning provides the policy, a patient digital twin pr…
Explainable Counterfactual Reasoning in Depression Medication Selection at Multi-Levels (Personalized and Population)
Xinyu Qin, Mark H. Chignell, Alexandria Greifenberger +5
Background: This study investigates how variations in Major Depressive Disorder (MDD) symptoms, quantified by the Hamilton Rating Scale for Depression (HAM-D), causally influence t…