1 citations · 1 across the 4 of their papers we have counts for
6 papers
EngageTriBoost: Predictive Modeling of User Engagement in Digital Mental Health Intervention Using Explainable Machine Learning
Ha Na Cho, Daniel Eisenberg, Cheryl King +1
Mental health challenges among young adults, are on the rise, necessitating effective solutions such as digital mental health interventions (DMHIs). Despite their promise, DMHIs fa…
Consumer-to-Clinical Language Shifts in Ambient AI Draft Notes and Clinician-Finalized Documentation: A Multi-level Analysis
Ha Na Cho, Yawen Guo, Sairam Sutari +5
Ambient AI generates draft clinical notes from patient-clinician conversations, often using lay or consumer-oriented phrasing to support patient understanding instead of standardiz…
Building Safe and Deployable Clinical Natural Language Processing under Temporal Leakage Constraints
Ha Na Cho, Sairam Sutari, Alexander Lopez +2
Clinical natural language processing (NLP) models have shown promise for supporting hospital discharge planning by leveraging narrative clinical documentation. However, note-based…
What Drives Length of Stay After Elective Spine Surgery? Insights from a Decade of Predictive Modeling
Ha Na Cho, Seungmin Jeong, Yawen Guo +3
Objective: Predicting length of stay after elective spine surgery is essential for optimizing patient outcomes and hospital resource use. This systematic review synthesizes computa…
When AI Writes Back: Ethical Considerations by Physicians on AI-Drafted Patient Message Replies
Di Hu, Yawen Guo, Ha Na Cho +7
The increasing burden of responding to large volumes of patient messages has become a key factor contributing to physician burnout. Generative AI (GenAI) shows great promise to all…
Barriers to Digital Mental Health Services among College Students
Ha Na Cho, Kyuha Jung, Daniel Eisenberg +2
This qualitative study explores barriers to utilization of digital mental health Intervention (DMHI) among college students. Data are from a large randomized clinical trial of an i…