Welcome to the Said lab
Our lab specializes in translational biomedical informatics, leveraging high-resolution electronic health record (EHR) data to develop machine learning-based, clinically applicable decision support tools.
Our research focuses on transforming large-scale health data into actionable insights that enhance patient care, with particular emphasis on creating innovative solutions that can be seamlessly integrated into clinical workflows.
Our research projects are at the forefront of leveraging data to develop life saving predictive models in the ICU.
Ahmed Said, MD, PhD
Principal investigator
Ahmed Said earned his medical degree, master’s and PhD while completing his pediatric residency and initial pediatric critical care training at Ain Shams University in Cairo, Egypt. During his PhD, he undertook research fellowship training at Washington University in St. Louis. Upon completion of his PhD, Said returned to Washington University and St. Louis Children’s Hospital for further training, completing a pediatric residency followed by a pediatric critical care fellowship, with advanced specialization in pediatric cardiac critical care. He joined the faculty in 2015.
Said currently serves as the medical co-director of the Extracorporeal Membrane Oxygenation (ECMO) program at St. Louis Children’s Hospital. He is also a faculty member at the Artificial Intelligence for Health Institute (AIHealth) and holds a research faculty position at the Institute for Informatics, Data Science and Biostatistics (I2DB) at Washington University in St. Louis.
His research focuses on translational biomedical informatics, particularly the integration of complex, high-volume electronic health record (EHR) data to develop machine learning models for clinical decision support. His ongoing projects include the development of predictive models to link ECMO utilization and timing with functional neurological outcomes, as well as the creation of clinical decision support tools for optimizing anticoagulation management in pediatric ECMO patients.