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We collaborate closely with clinicians at the PAI Lab to translate specialized medical knowledge into accessible software and mobile technologies. Our tools, powered by quantitative imaging and advanced machine learning, help pediatric specialists worldwide to enhance diagnostics and predict clinical outcomes in infancy and childhood diseases. Our technologies enable timely care delivery and prevent potential health complications by facilitating early diagnosis.
Our lab is dedicated to refining the clinical value of medical images to advance the health care for children. For the latest updates on our projects and breakthroughs, visit our research page.
For more information or to get involved: mlingura@childrensnational.org
Marius George Linguraru, D.Phil., M.A., M.S.
Principal Investigator and Director
Pediatric Accelerated Intelligence Lab
Sheikh Zayed Institute for Pediatric Surgical Innovation
Children's National Hospital
A step-by-step guide to deploying a browser-based 3D medical segmentation application
Official repository for "Diverse Concept Modeling (DiCoMX): Domain-specific self-supervised pre-training strategy for chest X-ray foundation models"
In-house trained AI model for equitable facial landmarking in children
Code to preprocess, segment, and fuse glioma MRI scans based on the BraTS Toolkit manuscript.
Synthesis of Pathological Dual-Channel Color Doppler Echocardiograms for Equitable Diagnosis of Heart Diseases
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