AIMC Topic: Population Surveillance
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Hip surveillance in children with cerebral palsy in the UK : history, challenges, and future directions.
The bone & joint journal
Jul 1, 2025
Cerebral palsy (CP) is associated with musculoskeletal complications in children, notably hip migration, which can progress to hip dislocation and joint degeneration. Without regular radiological monitoring, early-stage hip migration can be missed, p...
Changes in Epidemiological Characteristics of Varicella and Breakthrough Cases in Ningbo, China, From 2010 to 2023: Surveillance Study.
JMIR public health and surveillance
Jun 18, 2025
BACKGROUND: Varicella is a prevalent respiratory infectious disease. Continuous monitoring is essential to understand evolving epidemiological patterns, particularly given the impact of vaccination and recent nonpharmacological interventions.
Mandatory surveillance of bacteremia conducted by automated monitoring.
Frontiers in public health
Dec 16, 2024
Except for a few countries, comprehensive all-cause surveillance for bacteremia is not part of mandatory routine public health surveillance. We argue that time has come to include automated surveillance for bacteremia in the national surveillance sys...
Machine learning-based prediction of elevated N terminal pro brain natriuretic peptide among US general population.
ESC heart failure
Nov 19, 2024
AIMS: Natriuretic peptide-based pre-heart failure screening has been proposed in recent guidelines. However, an effective strategy to identify screening targets from the general population, more than half of which are at risk for heart failure or pre...
Recognition and segmentation of individual pigs based on Swin Transformer.
Animal genetics
Sep 22, 2022
Recognition of individual pigs is critical to the monitoring of pig body size and physiological health status in large-scale pig farms. In this study, deep learning methods were introduced in the intelligent recognition and segmentation of individual...
High-Efficiency Machine Learning Method for Identifying Foodborne Disease Outbreaks and Confounding Factors.
Foodborne pathogens and disease
Apr 26, 2021
The China National Center for Food Safety Risk Assessment (CFSA) uses the Foodborne Disease Monitoring and Reporting System (FDMRS) to monitor outbreaks of foodborne diseases across the country. However, there are problems of underreporting or errone...
A Machine Learning Approach to Management of Heart Failure Populations.
JACC. Heart failure
May 6, 2020
BACKGROUND: Heart failure is a prevalent, costly disease for which new value-based payment models demand optimized population management strategies.
Knowledge transfer as a tool towards improvement of cancer care in low- and middle-income countries. 6th European Roundtable Meeting (ERTM), June 14th, 2019, Berlin, Germany.
Journal of cancer research and clinical oncology
Apr 8, 2020
PURPOSE: To identify key factors for the best practice of knowledge transfer from high-income settings to low- and middle-income settings.
Disruptive Technologies for Environment and Health Research: An Overview of Artificial Intelligence, Blockchain, and Internet of Things.
International journal of environmental research and public health
Oct 11, 2019
The purpose of this descriptive research paper is to initiate discussions on the use of innovative technologies and their potential to support the research and development of pan-Canadian monitoring and surveillance activities associated with environ...
Artificial intelligence and avian influenza: Using machine learning to enhance active surveillance for avian influenza viruses.
Transboundary and emerging diseases
Aug 19, 2019
Influenza A viruses are one of the most significant viral groups globally with substantial impacts on human, domestic animal and wildlife health. Wild birds are the natural reservoirs for these viruses, and active surveillance within wild bird popula...
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