Deep Learning Model for Predicting Neurodevelopmental Outcome in Very Preterm Infants Using Cerebral Ultrasound
We developed and internally validated a DL prognostic model using CUS and clinical predictors to predict NDI in VPIs at 3 years of age. Early and accurate identification of infants at risk for NDI enables referral to targeted interventions, which improves functional outcomes.
Authors
- Alessandro Guida (ORCID: https://orcid.org/0000-0002-7160-750X)
- Jehier K. Afifi (ORCID: https://orcid.org/0000-0001-7651-3054)
- Tahani Ahmad (ORCID: https://orcid.org/0000-0001-9885-6090)
- Samuel A. Stewart (ORCID: https://orcid.org/0000-0001-6299-7967)
- Michael John Vincer (ORCID: https://orcid.org/0000-0001-8119-3286)
- N K Barrett
Institutions
- University of Jordan (JO)
- Dalhousie University (CA)
- Nova Scotia Hospital (CA)
- Izaak Walton Killam Health Centre (CA)
- Nova Scotia Health Authority (CA)
- Nova Scotia Department of Agriculture (CA)
Publication Details
- Journal
- Mayo Clinic Proceedings Digital Health
- Published
- 2024-10-09
- DOI
- https://doi.org/10.1016/j.mcpdig.2024.09.003
- Citations
- 1
- Primary Topic
- Neonatal and fetal brain pathology
- Type
- article
- Field-Weighted Citation Impact
- 1.11
Funders
- RSNA Research and Education Foundation
- Dalhousie University
- University of Toronto
- IWK Health Centre