Oral Presentation
March 22, 1:30 p.m. - 3:00 p.m.
- A Technical Performance Study and Proposed Systematic and Comprehensive Evaluation of an ML-based CDS Solution for Pediatric Asthma
Shauna Overgaard
- Prospective Evaluation of a 90-day Mortality Prediction Model: From Silent Pilots to Real Time Deployment in the EHR
Lorenzo Rossi
- A Holistic AI Evaluation Framework for Identifying Unrecognized Bias in Validated COVID-19 Prediction Models
Hossein Estiri
- Leveraging Explainable Machine Learning to Predict New Onset of ICU Delirium
Siru Liu
- Predictive Modeling of Periodontal Disease Risks Using Electronic Dental Records and Explainable Machine Learning
Jay Patel
Poster Sessions
March 21, 5:00 p.m. – 6:30 p.m.
March 22, 5:00 p.m. – 6:30 p.m.
- AI Showcase, Stage I, Technical Study: Lessons Learned from Developing and Deploying a Real-time Machine Learning Sepsis Prediction Model for Hematopoietic Cell Transplant Recipients
Zahra Eftekhari, City of Hope - AI-aided Genetic Diagnosis and Disease-gene Discovery: Scaling Up and Evaluation of an Automated Deep Phenotyping Algorithm on two External EHR Datasets
Ling Luo, National Library of Medicine, National Institutes of Health
- Augmenting the Quality Assurance Process with Human-centered Machine Learning in Radiation Oncology
Malvika Pillai, UNC Chapel Hill - Automated And Accessible Prediction of Progression in Age-related Macular Degeneration (AMD): External Validation from the Perspectives of Methods, Populations, and Users
Qingyu Chen, National Institutes of Health - Comparing Multiple Implementable Predictive Models for Pediatric Clinical Deterioration
Sameh Saleh, Children's Hospital of Philadelphia/University of Pennsylvania - A Deep Understanding Approach for Case Identification and Autocoding System of Cancer Pathology Reports for a Population Cancer Registry
*This presentation will not be presented onsite but will be part of the Digital Collection
Jon Patrick, Health Language Analytics Global - Developing a Chest Radiography Generative Adversarial Network (CXR-GAN) for Medical Education Simulation
Parth Shah, Perelman School of Medicine, University of Pennsylvania - Emergency Department Wait Time Prediction Based on Cyclical Features by Deep Neural Networks
*This presentation will not be presented onsite but will be part of the Digital Collection
Zhaohui Liang, York University - Evaluating the Translational Aspects of AI Application in Healthcare
Piyush Mathur, Cleveland Clinic - Evaluating Vendor-derived Pediatric Sepsis Predictive Model in Acute Care Settings
Feliciano Yu, Arkansas Children's Hospital
- I-WIN: an Intensive Care Warning INdex System for Early Prediction of Clinical deterioration and Intervention Using Data-driven Machine Learning Modeling of EHR Data
Fuchiang Rich Tsui, Children's Hospital of Philadelphia - A Multi-aspect Technical Performance Evaluation of Deep Learning Based Model For Predicting COVID-19 Patients Outcomes on Admission
Laila Rasmy, University of Texas Health Science Center in Houston
- Predicting Thirty-day Unplanned Cancer Readmissions using Machine Learning and Artificial Intelligence
Danny Wu, University of Cincinnati - Technical Performance Evaluation of a Deep Learning-based Vancomycin Therapeutic Drug Monitoring Model
Bingyu Mao, The University of Texas Health Science Center at Houston
- Towards an Optimal Policy of Mass Casualty Trauma Triage
Alexandrea Ramnarine, Northwestern University
