AIMC Topic: Population Surveillance

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The Development and Growth of the English National Real-Time Syndromic Surveillance Program: Key Developments and Lessons Learned From the First Two Decades.

Journal of medical Internet research
Syndromic surveillance now forms an integral part of the surveillance for a wide range of hazards in many countries. Establishing syndromic surveillance systems can be difficult due to the many different sources of data that can be used, cost pressur...

Hip surveillance in children with cerebral palsy in the UK : history, challenges, and future directions.

The bone & joint journal
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
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.

The future of healthcare-associated infection surveillance: Automated surveillance and using the potential of artificial intelligence.

Journal of internal medicine
Healthcare-associated infections (HAIs) are common adverse events, and surveillance is considered a core component of effective HAI reduction programmes. Recently, efforts have focused on automating the traditional manual surveillance process by util...

Mandatory surveillance of bacteremia conducted by automated monitoring.

Frontiers in public health
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
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
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
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
BACKGROUND: Heart failure is a prevalent, costly disease for which new value-based payment models demand optimized population management strategies.