Role of Artificial Intelligence in CXR interpretation in Pediatric Intensive Care Unit Ain Shams University

Abstract

his study (role of AI in CXR interpretation in PICU Ain shams university) is an analytical cross sectional study conducted by using the CXR done in the Ain shams universities hospitals PICU and transferred to the hospital PACS system. The study had significant insights to the AI and radiology communities in several ways. First, it has a large radiologist involvement in the design and execution of the study, indicating the integral role of radiologists and clinical experts in the development of AI algorithms. Overall in this study we found that the resident accuracy, sensitivity and time consumption improved across a large number of clinical chest x-ray findings when assisted by the deep-learning model. Effective implementation of the model has the potential to improve clinical practice. Research is underway to assess the generalizability of results to various clinical environments and health systems. We also raised the possibility of the potential use of AI systems in future radiology workflows for preliminary interpretations that target the most prevalent findings, leaving the final reads to be done by a more experienced radiologist in a suitable practice atmosphere to catch any potential misses from the less-prevalent fine-grained findings.