Latest AI and machine learning research in surveillance for healthcare professionals.
As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale ...
BACKGROUND: Avian influenza (AI) is an important zoonotic disease responsible for significant losses in most sub-Saharan countries. However, the role of poultry other than chicken in the epidemiology of the disease, especially after the first AI outbreak in Ghana, has not been fully elucidated. The obiective of this study is to determine whether the AI virus infection that was reported in the area...
BACKGROUND: Many electronic infection detection systems employ dichotomous classification methods, classifying patient data as pathological or normal ...
OBJECTIVE: Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in inj...
Comparative analyses of the characteristics of persons living with HIV infection (PLWH) in the United States (US) captured in surveillance and other o...
Structured reporting in medicine has been argued to support and enhance machine-assisted processing and communication of pertinent information. Retros...
We present a machine learning-based methodology capable of providing real-time ("nowcast") and forecast estimates of influenza activity in the US by l...
Person re-identification aims to match people across non-overlapping camera views, which is an important but challenging task in video surveillance. I...
BACKGROUND: Social media platforms are increasingly seen as a source of data on a wide range of health issues. Twitter is of particular interest for p...
Identifying populations of heart failure (HF) patients is paramount to research efforts aimed at developing strategies to effectively reduce the burde...
BACKGROUND: Death certificates provide an invaluable source for mortality statistics which can be used for surveillance and early warnings of increase...
BACKGROUND: Activities of daily living (ADL) are important for quality of life. They are indicators of cognitive health status and their assessment is...
BACKGROUND: Incidence of catheter-associated urinary tract infection (CAUTI) is a quality benchmark. To streamline conventional detection methods, an ...
For specific purpose, vision-based surveillance robot that can be run autonomously and able to acquire images from its dynamic environment is very imp...
BACKGROUND: In the past few decades, several researchers have proposed highly accurate prediction models that have typically relied on climate paramet...
BACKGROUND AND AIMS: The adenoma detection rate (ADR) is a quality metric tied to interval colon cancer occurrence. However, manual extraction of data...
OBJECTIVE: To synthesise recent research on the use of machine learning approaches to mining textual injury surveillance data.
The global movement of people and goods has increased the risk of biosecurity threats and their potential to incur large economic, social, and environ...
(Quantitative) structure activity relationship [(Q)SAR] modeling is the primary tool used to evaluate the mutagenic potential associated with drug imp...
It is well-known that a spontaneous reporting system suffers from significant under-reporting of adverse drug reactions from the source population. Th...