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In December 2021, the UN General Assembly adopted a resolution calling upon member states to strengthen health systems specifically to address the needs of individuals with rare genetic diseases. The mission of the Campbell Lab is to ensure that every child with a rare genetic disease is diagnosed as quickly and accurately as possible. By harnessing the power of the extensive data contained within the CHOP electronic health record (EHR), the lab uses state-of-the art techniques to define and diagnose rare, pediatric-onset genetic diseases.
Because of their rarity, our understanding of most genetic diseases is biased and incomplete. The lab uses less-biased EHR data to better understand the full scope genetic diseases’ features. From this, we can develop more evidence-based criteria for clinicians to make diagnoses clinically. We can also use statistical models and machine learning to automatically identify children potentially having a genetic disease.
Although substantial progress has been made in our ability to diagnose rare genetic disease, decades of research shows that genetic care and genetic testing is not equitably provided to patients who come from historically marginalized backgrounds. The lab also strives to understand the causes of these inequities and to intervene in the EHR to address them.
- Systematic automated extraction of phenotypes relevant to pediatric genetic disease using natural language processing and other machine learning from the EHR
- Developing evidenced-based methods of diagnosis of pediatric genetic disease
- Developing computational approaches to identifying children at risk of genetic disease
- Understanding barriers and addressing inequities in delivery of high-quality genetic care
- Implementation of clinical decision support in the EHR based on genetic disease
Assistant Professor of Pediatrics
Dr. Campbell is interested in approaches to improve diagnosis of children with rare genetic diseases. He also focuses on better understanding of the full spectrum of symptoms associated with genetic diseases as well as discovering new diseases.