AI-Based Prediction of Surfactant Need in Preterm Babies Using Clinical Data and Lung Ultrasound

A Occhipinti, LMT Doan, Y Karayaneva, O Ayobami, VV Kalva, C Angione, PK Loganathan

2026Medical Imaging Emotion Recognition and Brain Informatics

Abstract

Preterm infants frequently develop respiratory distress syndrome, requiring rapid decisions on surfactant therapy. Current assessment relies on subjective interpretation of lung ultrasound and heterogeneous clinical indicators, leading to variability in care. Hence, there is a need for objective, data-driven tools that integrate imaging and clinical data to support early, accurate prediction of surfactant requirement and improve neonatal outcome

Authors: Annalisa Occhipinti, Le Minh Thao Doan, Yordanka Karayaneva, Oki Ayobami, Vishnu Vardhan Kalva, Claudio Angione, Prakash Kannan Loganathan

Published in: Zenodo (CERN European Organization for Nuclear Research) (2026)

DOI · Google Scholar