A Simplified and Data‐Driven Lung Ultrasound Approach for Predicting Surfactant Need in Preterm Infants
A simplified, rule-based model that accounts for the differential predictive value of individual lung regions may enhance the accuracy of LUS-based prediction of surfactant need in preterm infants. It is also more accessible, effective, and time-efficient for clinicians.
Authors
- Bikash Bhojnagarwala
- Virginie Meau‐Petit (ORCID: https://orcid.org/0000-0002-2725-7522)
- Yogen Singh (ORCID: https://orcid.org/0000-0002-5207-9019)
- Mahmoud Montasser
- Prakash Kannan Loganathan (ORCID: https://orcid.org/0000-0003-3717-8569)
- Clemence Mottez (ORCID: https://orcid.org/0009-0009-3983-8461)
Institutions
- Durham University (GB)
- Cardiovascular Institute of the South (US)
- James Cook University Hospital (GB)
- Wishaw General Hospital (GB)
- Medway NHS Foundation Trust (GB)
- Institut Hospitalier Franco Britannique (FR)
- UC Davis Children's Hospital (US)
- Artificial Intelligence in Medicine (Canada) (CA)
- Newcastle University (GB)
- Stanford University (US)
Publication Details
- Journal
- Journal of Ultrasound in Medicine
- Published
- 2025-10-17
- DOI
- https://doi.org/10.1002/jum.70092
- Primary Topic
- Ultrasound in Clinical Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00