Johns Hopkins All Children's Hospital

AI/ML in Pediatric Research: Medical & Pharmaceutical Perspectives

Artificial Intelligence and Machine Learning in Pediatric Research Symposium

The Center for Pediatric Data Science and Analytics Methodology at Johns Hopkins All Children's Hospital in collaboration with the IQ Consortium, Pediatric Working Group is presented its annual Research Symposium: AI/ML in Pediatric Research on November 16, 2022. At this event, we  explored the relevance of AI/ML in developing better pharmaceuticals and discussed the implementation of AI/ML solutions in pediatric medicine.

 

Last Year's Topics and Speakers

Current State of Artificial Intelligence in Pediatric Medicine

Geoffrey M. Gray, Ph.D.
Assistant Professor, Anesthesiology and Critical Care Medicine, Johns Hopkins School of Medicine; Predictive Analytics Data Scientist, Center for Pediatric Data Science and Analytic Methodology, Johns Hopkins All Children’s Hospital

Current State of Artificial Intelligence in the Pharmaceutical Industry

Daniel Schaufelberger, Ph.D.
Adj. Assistant Professor, Johns Hopkins University, School of Medicine, Neurology; VP Chemistry, Manufacturing & Controls, NGT BioPharma Consultants LLC

Digital Assistant to Support Pharmaceutical Product Development

Sandip Tiwari, Ph.D.
Head of Technical Services—Pharma Solutions, North America, BASF Corporation

Assessing Palatability in Young Children: Purpose, Pitfalls and Potential

Gregory L. Kearns
Pharm.D., Ph.D., FAAP, FRSM Burnett School of Medicine at Texas Christian University, Fort Worth, TX

Big Data and Tiny Babies: How Can We Use Machine Learning to Answer Every Day Questions in the Neonatal Intensive Care Unit?

Rita Wyrebek M.D., MS
Neonatologist at SSM Health Cardinal Glennon Children’s Hospital; Assistant Professor of Pediatrics, Saint Louis University

AI in Medicine- Hype, Hope and Hurdles

Dr. Hannah Lonsdale MBChB
Assistant Professor, Department of Anesthesiology, Vanderbilt University Medical Center

Performance Characteristics of a Machine-Learning Tool to Predict 7-Day Hospital Readmissions

John M. Morrison M.D., Ph.D.
Johns Hopkins University School of Medicine, Johns Hopkins All Children’s Hospital

Chair

Geoffrey M. Gray, PhD 
Predictive Analytics Data Scientist 
Center for Pediatric Data Science and Analytic Methodology 
Johns Hopkins All Children's Hospital 
Assistant Professor 
Anesthesiology and Critical Care Medicine 
Johns Hopkins School of Medicine 

Co-Chairs

Luis M. Ahumada, MSCS, PhD 
Director Health Data Science & Analytics, Director Center for Pediatric Data Science and Analytic Methodology, Assistant Professor at Johns Hopkins University School of Medicine, Johns Hopkins All Children's Hospital  

Daniel Schaufelberger, PhD
Adj. Assistant Professor, Johns Hopkins University, School of Medicine, Neurology; VP Chemistry, Manufacturing & Controls, NGT BioPharma Consultants LLC