Today we are pleased to welcome a guest blog post from Santiago Ontañón, PhD, a research scientist and assistant professor at the College of Computing and Informatics at Drexel University. Dr. Ontañón led a study, “Learning to Predict Driver Behavior from Observation,” and recently presented on the findings at the Association for the Advancement of Artificial Intelligence (AAAI) Spring Symposia on Learning from Observation of Humans at Stanford University.
research tools and methods
A recent study taps useful research tools and data sources to shed light on the importance of strong state alcohol policies in preventing young people from dying in alcohol-related crashes.
Research participation is volunteerism! CHOP researchers deeply appreciate the contribution of families that chose to participate in studies, leading to breakthroughs and innovation daily.
Read about new CIRP@CHOP research about a tool that can help busy clinicians, school nurses, and others seeing in service settings screen for posttraumatic stress in children.
Read about a new CHOP study published in the Journal of Attention Disorders that validated an electronic health record (EHR)–based algorithm to classify the ADHD status of pediatric patients, which is part of a larger retrospective cohort study that aims to examine the association between ADHD and driving outcomes among adolescents.
Learn about a new CIRP@CHOP research tool that aims to help researchers better understand how parents and children interact after an injury.
Today we welcome a guest blog from Chris Gantz, MBA, program manager, Clinical Research Support Office, Recruit Enhancement Core, The Children’s Hospital of Philadelphia Research Institute, who shares why social media and mobile technology are creating opportunities to engage with potential study participants in ways that were not possible just a few years ago.
New CIRP@CHOP research proposes a novel approach to estimating compliance with Graduated Driver Licensing (GDL) laws.
CIRP@CHOP's academic-government collaboration can serve as a model for other states that are interested in optimizing the value of their administrative traffic safety data to inform state activities.
Learn why research is needed on automated car technology with teen drivers in mind to make the roads safer for everyone.