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To what extent are digital health interventions targeting HIV care cascade among mobile populations feasible, acceptable, and effective? A mixed methods systematic review protocol.
Syst Rev
January 2025
Division of Epidemiology & Biostatistics, School of Public Health, University of Cape Town, Cape Town, South Africa.
Introduction: Human mobility is associated with an increased risk of HIV acquisition and disengagement from HIV care, leading to poorer health outcomes among highly mobile individuals compared to less mobile individuals. Mobile individuals, broadly defined as those who temporally, seasonally, or permanently move from one place to another for voluntary or involuntary reasons, face many challenges in accessing HIV care services. These challenges include logistical difficulties, interruptions in HIV care continuity, and limited access to services across different locations, which together hinder timely testing, treatment initiation, and viral suppression.
View Article and Find Full Text PDFDiscovering patient groups in sequential electronic healthcare data using unsupervised representation learning.
BMC Med Inform Decis Mak
January 2025
Great Ormond Street Institute of Child Health, University College London, London, UK.
Introduction: Unsupervised feature learning methods inspired by natural language processing (NLP) models are capable of constructing patient-specific features from longitudinal Electronic Health Records (EHR).
Design: We applied document embedding algorithms to real-world paediatric intensive care (PICU) EHR data to extract patient-specific features from 1853 patients' PICU journeys using 647 unique lab tests and medication events. We evaluated the clinical utility of the patient features via a K-means clustering analysis.
Artificial intelligence methods applied to longitudinal data from electronic health records for prediction of cancer: a scoping review.
BMC Med Res Methodol
January 2025
Leeds Institute of Clinical Trials Research, University of Leeds, Clarendon Way, Leeds, LS2 9NL, UK.
Background: Early detection and diagnosis of cancer are vital to improving outcomes for patients. Artificial intelligence (AI) models have shown promise in the early detection and diagnosis of cancer, but there is limited evidence on methods that fully exploit the longitudinal data stored within electronic health records (EHRs). This review aims to summarise methods currently utilised for prediction of cancer from longitudinal data and provides recommendations on how such models should be developed.
View Article and Find Full Text PDFChildhood BMI trajectories and sociodemographic factors in an Italian pediatric population.
Sci Rep
January 2025
Unit of Biostatistics, Epidemiology and Public Health, Department of Cardio-Thoraco- Vascular Sciences and Public Health, University of Padua, Padua, Italy.
Childhood obesity is a growing global concern due to its long-term health consequences. Yet, more research relying on multiple time-point BMI measurements is warranted to gain further insight into obesity's temporal trends. We aimed to identify BMI trajectories in children aged 2-10 years and evaluate their association with sociodemographic factors.
View Article and Find Full Text PDFHealth risk assessment of dietary cadmium exposure based on cadmium bioavailability in food: Opportunities and challenges.
J Hazard Mater
January 2025
Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China. Electronic address:
Long-term exposure to Cd through contaminated food can lead to multiple adverse health effects on humans. Although previous studies have covered global food Cd concentrations and dietary Cd exposures across different populations, there are increasing concerns regarding the adequacy of current food Cd safety standards to protect populations from adverse health effects. Moreover, incorporation of Cd relative bioavailability (Cd-RBA) in foods improves the accuracy of health risk assessment.
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