Infervision has fostered a strong partnership with Sant Joan de Déu Barcelona Children's Hospital (SJD), one of Europe’s leading hospitals for children, adolescent and mother care. Since October 2018, SJD Hospital has started the validation of Infervision’s InferRead DR product in the pediatric population of 8 to 18 years old. With this partnership, Infervision aims to become one of the pioneers of AI applications in pediatrics.
SJD Barcelona Children's Hospital is a private, non-profit institution that is dedicated to public service, and has become one of the top 3 specialized pediatric centers in Spain. It is a member of the Brothers Hospitallers of Saint John of God, which manages more than 300 healthcare centers in 50 countries around the world .
Each year SJD Barcelona Children's Hospital performs more than 5,000 CT scans and 6,000 MRIs . Interestingly, the diagnostic and MRI area have been transformed into a “space odyssey,” with the MRI machine decorated like a rocket. Distracted by this imaginative play, the children become less frightened. According to Dr. Maria Teresa Maristany, head of the Diagnostic Imaging Department, this has resulted in an 18% decrease in the use of anesthesia .
MRI area at SJD Barcelona Children's Hospital 
Many hospitals in Spain and around the world lack of pediatric departments and there is a shortage of radiology consultants specialized in pediatrics. For instance, in the UK, around 10% of the unfilled radiology consultant posts are from pediatric radiology . AI products could help in reducing intraregional differences in pediatric services across Spain due to the lack of specialists.
Besides, research literature production on AI use in pediatrics is very limited . In this regard, the partnership between SJD Barcelona Children's Hospital and Infervision could contribute to detecting chest pathologies such as lung nodules, pneumonia, pleural effusion from pediatric chest x-ray images through convolutional neural networks.
Infervision’s server in SJD Barcelona Children's Hospital
The ultimate goal is to test whether AI leads to more accurate and faster diagnoses, increases sensitivity and specificity, and improves clinical outcomes. This could be translated into less adverse events, less readmissions and lower costs in pediatric centers.
Last but not least, AI could also contribute to writing new guidelines in pediatrics. For instance, clinical guidelines that define the correct size of a newborn skull are supported by studies with a small number of cases. With that in mind, AI could create new descriptions of clinical features through data analysis, pattern discovery and associations. Furthermore, the next step would be to use AI to match individual needs of patients with the best available intervention.