Artificial Intelligence and Data Analytics for Infectious Diseases Investigation and Control
A special issue of Tropical Medicine and Infectious Disease (ISSN 2414-6366). This special issue belongs to the section "Infectious Diseases".
Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 5241
Special Issue Editors
Interests: infectious diseases; vaccination; social media; machine learning; public health; informatics
Interests: health informatics; data analytics; machine learning; e-Health decision support; digital public health surveillance
Special Issue Information
Dear Colleagues,
Infectious diseases cause significant health, social, and economic impacts each year, with malaria, tuberculosis, and HIV/AID consistently listed in the top 10 causes of death worldwide. As well as the ongoing impact, infectious diseases can lead to large-scale pandemics, as highlighted by COVID-19, which has led to more than 6 million deaths since 2020.
Artificial intelligence (AI), machine learning, and novel data analytics offer new methods of data analysis which may assist in the monitoring and control of infectious diseases. Specifically, these methods have shown to be useful in the prediction and detection of infectious diseases, as well identifying those most at risk of disease. These methods allow the use of large datasets that have been underutilised with traditional surveillance and epidemiological methods. Data used to date includes hospitalisations, genomic data and other health datasets, demographic data, social media data, and spatial data.
This Special Issue will focus on highlighting novel applications of AI and machine learning to improve the investigation and control of infectious diseases. We invite submissions from researchers regarding novel uses of AI and machine learning in infectious disease investigation and control, as well as review articles discussing future opportunities and challenges in this emerging area of research.
Dr. Amalie Dyda
Dr. Anthony Nguyen
Guest Editors
Manuscript Submission Information
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Keywords
- infectious diseases
- machine learning
- artificial intelligence
- surveillance
- epidemiology
- clinical decision support
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