Diagnostic electron microscopy (EM) is indispensable in all cases of infectious diseases which deserve or profit from the detection of the entire pathogen (i.e. the infectious unit). The focus of its application has shifted during the last decades fr...
Infectious diseases are a global public health problem that poses a threat to human society. Since the 1970s, constantly mutated new infectious viruses have been quietly attacking humanity, and at least one new type of infectious disease is discovere...
Infectious diseases (London, England)
Nov 14, 2024
Infectious diseases remain a global health challenge, necessitating innovative approaches for their early diagnosis and effective treatment. Artificial Intelligence (AI) has emerged as a transformative force in healthcare, offering promising solution...
Infectious diseases, driven by a diverse array of pathogens, can swiftly undermine public health systems. Accurate diagnosis and treatment of infectious diseases-centered around the identification of biomarkers and the elucidation of disease mechanis...
As the influence and risk of infectious diseases increase, efforts are being made to predict the number of confirmed infectious disease patients, but research involving the qualitative opinions of social media users is scarce. However, social data ca...
Cambodia has made progress in reducing the under-five mortality rate and burden of infectious diseases among children over the last decades. However the determinants of child mortality and morbidity in Cambodia is not well understood, and no recent a...
BACKGROUND: Assessment of artificial intelligence (AI)-based models across languages is crucial to ensure equitable access and accuracy of information in multilingual contexts. This study aimed to compare AI model efficiency in English and Arabic for...
Infectious diseases are a major threat for human and animal health worldwide. Artificial Intelligence (AI) combined algorithms including Machine Learning and Big Data analytics have emerged as a potential solution to analyse diverse datasets and face...
OBJECTIVE: This study focuses on enhancing the precision of epidemic time series data prediction by integrating Gated Recurrent Unit (GRU) into a Graph Neural Network (GNN), forming the GRGNN. The accuracy of the GNN (Graph Neural Network) network wi...
BACKGROUND: Natural Language Processing (NLP) and Large Language Models (LLMs) hold largely untapped potential in infectious disease management. This review explores their current use and uncovers areas needing more attention.
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