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AIDS Behav
January 2025
Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA.
Longitudinal patterns of engagement in care among women living with HIV (WHIV) during the perinatal period are poorly understood. We employed group-based trajectory modeling to (1) describe trajectories of HIV visit engagement; and (2) identify predictors of membership in suboptimal care trajectories. Data came from a prospective cohort study across five urban clinics in Lilongwe, Malawi conducted between February 2020 and August 2022.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
We aimed to develop and evaluate Explainable Artificial Intelligence (XAI) for fetal ultrasound using actionable concepts as feedback to end-users, using a prospective cross-center, multi-level approach. We developed, implemented, and tested a deep-learning model for fetal growth scans using both retrospective and prospective data. We used a modified Progressive Concept Bottleneck Model with pre-established clinical concepts as explanations (feedback on image optimization and presence of anatomical landmarks) as well as segmentations (outlining anatomical landmarks).
View Article and Find Full Text PDFPLoS One
January 2025
School of Women's and Children's Health, University of New South Wales, Sydney, Australia.
Background: Antenatal care (ANC) coverage in low- and middle-income countries has increased in the past few decades. However, merely increasing care coverage may not enhance maternal and newborn health unless the recommended service components are also provided. Our aim was to assess the quality of ANC and its associated factors in Ethiopia.
View Article and Find Full Text PDFChin Med J (Engl)
January 2025
Department of Medical Genetics/Prenatal Diagnostic Center, West China Second University Hospital, Sichuan University, Chengdu, Sichuan 610000, China.
J Glob Health
January 2025
Rural Health Research Institute, Charles Sturt University, Orange, New South Wales, Australia.
Background: Identifying the modifiable risk factors for childhood mortality using population-attributable fractions (PAFs) estimates can inform public health planning and resource allocation in low- and middle-income countries (LMICs). We estimated PAFs for key population-level modifiable risk factors of neonatal, infant, and under-five mortality in LMICs.
Methods: We used the most recent Demographic and Health Survey data sets (2010-22) from 48 LMICs, encompassing 35 sub-Saharan African countries and 13 countries from South and Southeast Asia (n = 506 989).
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