Public Health

The Detection of Opioid Misuse and Heroin Use From Paramedic Response Documentation: Machine Learning for Improved Surveillance.

BACKGROUND: Timely, precise, and localized surveillance of nonfatal events is needed to improve response and prevention of opioid-related problems in an evolving opioid crisis in the United States. Records of naloxone administration found in prehospital emergency medical services (EMS) data have helped estimate opioid overdose incidence, including nonhospital, field-treated cases. However, as nalo...

Unsupervised machine learning for the discovery of latent disease clusters and patient subgroups using electronic health records.

Machine learning has become ubiquitous and a key technology on mining electronic health records (EHRs) for facilitating clinical research and practice. Unsupervised machine learning, as opposed to supervised learning, has shown promise in identifying novel patterns and relations from EHRs without using human created labels. In this paper, we investigate the application of unsupervised machine lear...

Annual Report on surveillance for avian influenza in poultry and wild birds in Member States of the European Union in 2018.

Avian influenza (AI) is a viral infectious disease that affects all species of domestic and wild birds. The viruses causing this disease can be of hig...

Broad-specificity ELISA with a heterogeneous strategy for sensitive detection of microcystins and nodularin.

A highly sensitive and broadly specific competitive indirect enzyme-linked immunosorbent assay (ciELISA) method was developed for the simultaneous det...

Location of sources in reaction-diffusion equations using support vector machines.

The reaction-diffusion equation serves to model systems in the diffusion regime with sources. Specific applications include diffusion processes in che...

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...

The use of natural language processing to identify vaccine-related anaphylaxis at five health care systems in the Vaccine Safety Datalink.

PURPOSE: The objective was to develop a natural language processing (NLP) algorithm to identify vaccine-related anaphylaxis from plain-text clinical n...

Identifying undetected dementia in UK primary care patients: a retrospective case-control study comparing machine-learning and standard epidemiological approaches.

BACKGROUND: Identifying dementia early in time, using real world data, is a public health challenge. As only two-thirds of people with dementia now ul...

Decision tree machine learning applied to bovine tuberculosis risk factors to aid disease control decision making.

Identifying and understanding the risk factors for endemic bovine tuberculosis (TB) in cattle herds is critical for the control of this disease. Explo...

Verification with the utility of an established rapid assessment of brain safety for newly developed vaccines.

In the twenty-first century, high contagious infectious diseases such as SARS (Severe Acute Respiratory Syndrome), MERS (Middle East Respiratory Syndr...

Digital Health Consumers on the Road to the Future.

Digital health is uniquely positioned to transform health care. This viewpoint explores the enormous benefits for health consumers when digital-first ...

Local distinguishability aggrandizing network for human anomaly detection.

With the growing demand for an intelligent system to prevent abnormal events, many methods have been proposed to detect and locate anomalous behaviors...

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...

Peptide arrays incubated with three collections of human sera from patients infected with mosquito-borne viruses.

Global outbreaks caused by emerging or re-emerging arthropod-borne viruses (arboviruses) are becoming increasingly more common. These pathogens inclu...

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, ...

Spatiotemporal dengue fever hotspots associated with climatic factors in Taiwan including outbreak predictions based on machine-learning.

Early warning systems (EWS) have been proposed as a measure for controlling and preventing dengue fever outbreaks in countries where this infection is...

Automatically Appraising the Credibility of Vaccine-Related Web Pages Shared on Social Media: A Twitter Surveillance Study.

BACKGROUND: Tools used to appraise the credibility of health information are time-consuming to apply and require context-specific expertise, limiting ...

The FluPRINT dataset, a multidimensional analysis of the influenza vaccine imprint on the immune system.

Machine learning has the potential to identify novel biological factors underlying successful antibody responses to influenza vaccines. The first atte...

Using satellite-measured relative humidity for prediction of Metisa plana's population in oil palm plantations: A comparative assessment of regression and artificial neural network models.

Metisa plana (Walker) is a leaf defoliating pest that is able to cause staggering economical losses to oil palm cultivation. Considering the economic ...

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...