.Alex Towbin (He/Him) describes the imaging value chain from the patient's perspective. He stresses that we should strive to engage in our patients at each step of this chain. Read his Pediatric Radiology article entitled "Using informatics to engage patients" pubmed.ncbi.nlm.nih.gov/32935243/ #RSNA21

RECRUITING #DeepLearning #Data Scientist / #AI Expert / Research Fellow Interested in image-based AI? Come join our team!

Thanks to @SocAbdRadiology for recognizing our research as best emerging science/technology scientific session presentation #SAR2022 #MRI #Crohn Truly a team effort! Hailong Li Lili He Cincinnati Children's Schubert-Martin IBD Center Cincy Kids Radiology

Congratulations to ⁦Jonathan Dillman⁩, ⁦Lili He⁩, ⁦Hailong Li⁩, ⁦Elanchezhian Somasundaram⁩, ⁦Samuel Brady PhD⁩ and other authors for being awarded the Walter Berdon Award for Best Scientific Paper in ⁦Pediatric Radiology⁩ #SPR22

Happy to present in NeuroImage a novel ontology-guided ensemble learning method model to predict #CognitiveDeficits at 2 years of age using quantitative #structuralMRI obtained at term equivalent age in #VeryPretermInfants. sciencedirect.com/science/articl…

Excited to share our new NeuroImage pub which argues that DEHSI/diffuse white matter abnormality (DWMA) on MRI in Antoinette is the neuroimaging correlate of diffuse WM gliosis doi.org/10.1016/j.neur… #CINEPS @TimBonfield Lili He Hailong.Li James P Boardman Atul Malhotra

The Lili He lab is presenting the first of two #RSNA22 presentations. This will occur in the Learning Center, M5A-SPIN-2

Self-supervised learning is a cutting edge machine learning technique. Of course the Lili He lab is leading the way #RSNA22

The goal of this project is to develop an early prediction mode for cognitive development based on neonatal MRI #RSNA22

It's amazing how Lili He knows how to simplify a massive machine learning project #RSNA22

Naturally, the Lili He algorithm performed superbly #RSNA22

This type of feature visualization reminds us of the Ishihara test for color blindness #RSNA22

The Lili He lab confirms that their AI model is first-rate #RSNA22

Live feed from the #RSNA22 crowd after watching the Lili He presentation

congrats @reda_902006 Hailong Li Jonathan Dillman

A significant finding from Nehal Parikh, DO, MS group — Preterm birth • Smoking during pregnancy • Brain abnormalities on MRI at term

Redha Ali will describe a transformer- based framework for liver stiffness classification in children. This is one of many collaboration's between our department, NYU Langone Health Department of Radiology, @UmichRadiology, and UW Radiology Jonathan Dillman @hailongli_oh Lili He #ISMRM23 #ISMRM2023 🧵

This Hailong Li poster will describe how he stratified liver fibrosis using machine learning and radiomic data. This is one of many collaboration's between our department, NYU Langone Health Department of Radiology, @UmichRadiology, and UW Radiology Jonathan Dillman Lili He #ISMRM23 #ISMRM2023 🧵

Can cognitive defects be predicted using multimodal MRI and clinical data? It got to see this #ISMRM23 #ISMRM2023 presentation to learn the answer Jonathan Dillman Lili He Hailong Li 🧵

Huixian Zhang shares work describing simultaneous liver & spleen segmentation on T1 and T2 images. This is another of our famous collaborations with NYU Langone Health Department of Radiology, @UmichRadiology, and UW Radiology Hailong Li Jonathan Dillman Lili He #ISMRM23 #ISMRM2023 🧵