Work

Artificial Intelligence Outcome Prediction in Neonates with Encephalopathy (AI-OPiNE)

Year: 2024

Type: article

Abstract: To develop a deep learning algorithm to predict 2-year neurodevelopmental outcomes in neonates with hypoxic-ischemic encephalopathy using MRI and basic clinical data.

Source: Radiology Artificial Intelligence

DOI: 10.1148/ryai.240076

Authors: Christopher O. Lew, Evan Calabrese, Joshua V. Chen, Felicia Tang, Gunvant Chaudhari, Amanda Lee, John Faro, Sandra Juul, Amit Mathur, Robert C. McKinstry, Jessica L. Wisnowski, Andreas Rauschecker, Yvonne W. Wu, Yi Li

Institutions: University of Southern California, University of California, San Francisco, University of Washington, Duke Medical Center, Saint Louis University

Language: English

Topic: Neonatal and fetal brain pathology

Subfield: Pediatrics, Perinatology and Child Health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Heart, Lung, and Blood Institute, National Institute of General Medical Sciences, National Institute of Neurological Disorders and Stroke, Eunice Kennedy Shriver National Institute of Child Health and Human Development

Awards: G1185693225, G1631241416, G2571497891, G4190884620, G4303275075, G4885985545, Intellectual and Developmental Disabilities Research Center, High-dose Erythropoietin for Asphyxia and Encephalopathy (HEAL) CCC

OpenAlex ID: W4400495194

FWCI: 13.32

Cites: 33

Cited by: 22

Related to: 10