November 8, 2022 | 8:30 a.m. – 10:30 a.m.
Evaluating Deterioration Prediction, Usability, and Impact of a Clinical Artificial Intelligence System: Real-time Intensive Care Warning INdex System (I-WIN) Using EHR and Bedside Monitor Data
- Fuchiang (Rich) Tsui, Children's Hospital of Philadelphia
Enhancing an AI-Empowered Periodontal CDSS and Comparing with Traditional Perio-risk Assessment Tools
- Jay Patel, Temple University
Evaluation of the Impact of a 90-day Mortality Prediction Model Integrated in the EHR for Advanced Care Planning
- Lorenzo Rossi, City of Hope National Medical Center
Development of a Clinical Decision Support System to Predict Unplanned Cancer Readmissions
- Danny Wu, University of Cincinnati College of Medicine
November 7, 2022 | 5:00 p.m. – 6:30 p.m.
November 8, 2022 | 5:00 p.m. – 6:30 p.m.
A Deductive Data-Driven Pipeline Powered by MLHO for Post-Acute Sequelae of COVID-19 (PASC) Phenotyping
- Arianna Dagliati, university of Pavia
Comprehensive Evaluation of Health Impact of an ML-Based CDS Solution Integrated with Remote Device: Protocol for RCT in Children with Asthma
- Lynnea Myers, Mayo Clinic, Karolinska Institutet
Automated and accessible diagnosis of age-related macular degeneration: a comparative analysis of the impact of machine learning models in clinical diagnostic workflows
- Qingyu Chen, National Institutes of Health
Healthcare Impacts of Real-Time Sepsis Risk Prediction Workflows for Hematopoietic Cell Transplant Recipients
- Cameron Carlin, City of Hope National Medical Center
A Theory-based Evaluation of a Clinical Decision Support System to Predict New Onset of Delirium
- Siru Liu, Vanderbilt University
Evaluating a vendor-derived pediatric sepsis predictive model in acute care settings
- Daniel Liu, University of Arkansas for Medical Sciences