Latest AI and machine learning research in public health & policy for healthcare professionals.
The prevention and control of odor gas generated from kitchen waste are significant missions in rese...
BackgroundAnalysis of data from incident registries such as MAUDE has identified the need to improve...
Fraud detection for imbalanced datasets is challenging due to machine learning models inclination to...
BACKGROUND: The global outbreak of the coronavirus disease 2019 (COVID-19) has been enormously damag...
BACKGROUND: Injuries constitute a significant global public health concern, particularly among indiv...
The integration of Artificial Intelligence (AI) and Intelligent Learning Models (ILMs) in healthcare...
BACKGROUND: Social networking services (SNS) closely reflect the lives of individuals in modern soci...
Brain metastases (BMs) in extensive-stage small cell lung cancer (ES-SCLC) are often associated with...
Several pieces of evidence have been reported regarding the association between periodontitis and sy...
In this narrative review, we review the applications of artificial intelligence (AI) into clinical m...
The fire safety compliance checking (FSCC) plays a crucial role in ensuring the quality of fire engi...
Specifying and interpreting the occurrence of emerging pollutants is essential for assessing treatme...
Infectious diseases remain a global health challenge, necessitating innovative approaches for their ...
In recent years, public health events have significantly impacted various aspects of human productio...
In Africa, livestock production plays a crucial role for sustainable food security and economic grow...
Tuberculosis (TB), the second leading infectious killer globally, claimed the lives of 1.3 million i...
Some of the early applications of artificial intelligence (AI) for food safety appear to be intended...
Accurate counting of mosquito larval populations is essential for maintaining optimal conditions and...
The COVID-19 outbreak caused saturations of hospitals, highlighting the importance of early patient ...
In causal inference, parametric models are usually employed to address causal questions estimating t...
OBJECTIVE: Active adverse event surveillance monitors Adverse Drug Events (ADE) from different data ...