Statistical learning to identify and characterise neurodevelopmental outcomes at 2 years in babies born preterm: model development and validation using population-level data from England and Wales
Statistical learning to identify and characterise neurodevelopmental outcomes at 2 years in babies born preterm: model development and validation using population-level data from England and Wales
Sadia Haider, Cheryl Battersby, James P. Boardman, Riccardo E. Marioni et al.
Citations
3 citations
Journal
EBioMedicine
Topics
Infant Development and Preterm Care
Field-Weighted Citation Impact (FWCI)
10.48
article
Statistical learning to identify and characterise neurodevelopmental outcomes at 2 years in babies born preterm: model development and validation using population-level data from England and Wales
Sadia Haider, Cheryl Battersby, James P. Boardman, Riccardo E. Marioni, Simon R. Cox, Athanasios Tsanas, G. David Batty, Rebecca M. Reynolds, Heather C. Whalley
article en
3 citations
Abstract
No abstract available for this paper.
Publication Tag
EBioMedicineVol. 117
Institutions
Turing Institute (GB), NHS Lothian (GB), Edinburgh Cancer Research (GB), MRC Centre for Regenerative Medicine (GB), MRC Centre for Reproductive Health (GB), The Queen's Medical Research Institute (GB), University College London (GB), Imperial College London (GB), University of Edinburgh (GB)
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Statistical learning to identify and characterise neurodevelopmental outcomes at 2 years in babies born preterm: model development and validation using population-level data from England and Wales — Sadia Haider, Cheryl Battersby, et al. · EBioMedicine (2025) | TGRS Research Map | TGRS