Surveillance

Pharmacokinetic-pharmacodynamic assessment of the ivermectin and abamectin nematodicidal interaction in cattle.

In a context of nematodicidal resistance, anthelmintic combinations have emerged as a reliable pharmacological strategy to control gastrointestinal nematodes in grazing systems of livestock production. The current work evaluated the potential drug-drug interactions following the coadministration of two macrocyclic lactones (ML) ivermectin (IVM) and abamectin (ABM) to parasitized cattle using a pha...

Spatial Lifecourse Epidemiology Reporting Standards (ISLE-ReSt) statement.

Spatial lifecourse epidemiology is an interdisciplinary field that utilizes advanced spatial, location-based, and artificial intelligence technologies to investigate the long-term effects of environmental, behavioural, psychosocial, and biological factors on health-related states and events and the underlying mechanisms. With the growing number of studies reporting findings from this field and the...

A comparison of statistical and machine learning methods for creating national daily maps of ambient PM concentration.

A typical challenge in air pollution epidemiology is to perform detailed exposure assessment for individuals for which health data are available. To a...

Deep learning for pollen allergy surveillance from twitter in Australia.

BACKGROUND: The paper introduces a deep learning-based approach for real-time detection and insights generation about one of the most prevalent chroni...

Detecting motorcycle helmet use with deep learning.

The continuous motorization of traffic has led to a sustained increase in the global number of road related fatalities and injuries. To counter this, ...

The robustness-fidelity trade-off in Grow When Required neural networks performing continuous novelty detection.

Novelty detection allows robots to recognise unexpected data in their sensory field and can thus be utilised in applications such as reconnaissance, s...

Antibiotic therapy in patients with high prostate-specific antigen: Is it worth considering? A systematic review.

: To address the question of whether antibiotic therapy can obviate the need for prostate biopsy (PBx) in patients presenting with high prostate-speci...

Disruptive Technologies for Environment and Health Research: An Overview of Artificial Intelligence, Blockchain, and Internet of Things.

The purpose of this descriptive research paper is to initiate discussions on the use of innovative technologies and their potential to support the res...

Classification of Cancer at Prostate MRI: Deep Learning versus Clinical PI-RADS Assessment.

Background Men suspected of having clinically significant prostate cancer (sPC) increasingly undergo prostate MRI. The potential of deep learning to p...

Formalizing video documentation of the Critical View of Safety in laparoscopic cholecystectomy: a step towards artificial intelligence assistance to improve surgical safety.

BACKGROUND: In laparoscopic cholecystectomy (LC), achievement of the Critical View of Safety (CVS) is commonly advocated to prevent bile duct injuries...

Machine Learning in Epidemiology and Health Outcomes Research.

Machine learning approaches to modeling of epidemiologic data are becoming increasingly more prevalent in the literature. These methods have the poten...

A comparison of machine learning algorithms for the surveillance of autism spectrum disorder.

OBJECTIVE: The Centers for Disease Control and Prevention (CDC) coordinates a labor-intensive process to measure the prevalence of autism spectrum dis...

Symmetry of generalized rivalry network models determines patterns of interocular grouping in four-location binocular rivalry.

Previously, symmetry of network models has been proposed to account for interocular grouping during binocular rivalry. Here, we construct and analyze ...

Comprehensive analysis of machine learning models for prediction of sub-clinical mastitis: Deep Learning and Gradient-Boosted Trees outperform other models.

Sub-clinical bovine mastitis decreases milk quality and production. Moreover, sub-clinical mastitis leads to the use of antibiotics with consequent in...

A dynamic neural network model for predicting risk of Zika in real time.

BACKGROUND: In 2015, the Zika virus spread from Brazil throughout the Americas, posing an unprecedented challenge to the public health community. Duri...

Machine-learning algorithms to identify key biosecurity practices and factors associated with breeding herds reporting PRRS outbreak.

Investments in biosecurity practices are made by producers to reduce the likelihood of introducing pathogens such as porcine reproductive and respirat...

Artificial intelligence and avian influenza: Using machine learning to enhance active surveillance for avian influenza viruses.

Influenza A viruses are one of the most significant viral groups globally with substantial impacts on human, domestic animal and wildlife health. Wild...

Lessons learned from the application of machine learning to studies on plant response to radio-frequency.

This paper applies Machine Learning (ML) algorithms to peer-reviewed publications in order to discern whether there are consistent biological impacts ...

Public Health and Epidemiology Informatics: Can Artificial Intelligence Help Future Global Challenges? An Overview of Antimicrobial Resistance and Impact of Climate Change in Disease Epidemiology.

OBJECTIVES: To provide an oveiview of the current application of artificial intelligence (AI) in the field of public health and epidemiology, with a s...

Artificial Intelligence for Surveillance in Public Health.

OBJECTIVES: To introduce and summarize current research in the field of Public Health and Epidemiology Informatics.