Infectious Disease and AI: Preparing For "Disease X"
Discover how AI enhances medical imaging and disease classification, contributing to pandemic preparedness and infectious disease management.
11/3/20242 min read
Author: Koyi Ugboma MD, MSc, LLM, MBA
A future global epidemic, which epidemiologists predict may occur on a scale similar to COVID-19, is anticipated. The estimated likelihood of this event is 1 in 4, though the specifics of this epidemic remain unknown. AI is positioned to provide early warnings through data analysis, aiding in the prediction of such an outbreak.
AI's role extends beyond outbreak prediction; it also helps in identifying antibodies essential for vaccine production. These antibodies are the building blocks of the immune system that fights diseases.
The Coalition for Epidemic Preparedness Innovations (CEPI), which currently funds EVEScape, believes AI will be crucial in preparing for future epidemics and improving the global response.
The World Health Organization (WHO), through its Intelligence, Innovation, and Integration unit, is capable of detecting early symptoms and threats, issuing early warnings. This use of AI places the global community in a stronger position than before to predict, manage, and treat epidemic outcomes.
Key Benefits of AI in Infectious Disease Control
AI enhances structured decision-making, leading to:
Early warning by distinguishing various pathogen and virus subtypes.
Enhanced forecasting capabilities.
Improved classification of diseases and treatments.
Better prevalence monitoring and early detection.
Efficient resource allocation
Imaging capabilities for rapid evaluation and classification of images.
AI in Medical Imaging for Infectious Diseases
Medical imaging is another area where AI is making significant contributions. As described by Winston T. Chi et al. in the Journal of Infectious Diseases, AI-driven imaging proves valuable in pandemic data science. It employs tools for quantitative, semi-automated measurement, classification, and interpretation of medical images, leading to machine learning-based disease classification.
Moreover, time series and 3D images can be processed through AI-driven data analysis, allowing complex information to be harnessed more quickly and effectively.
Machine Learning has used numerous algorithms to improve the classification and identification of images associated with Infectious diseases.
Conclusion
AI has demonstrated its potential to enhance early detection of infectious diseases, from predicting various subtypes to allocating resources and managing disease presentations. AI has transformed the landscape of infectious disease preparedness, helping the global community prepare for the next epidemic more effectively.
Further Reading
The rise of AI reading of Chest X-rays for enhanced TB diagnosis and Elimination Geric.C et.al
Vallerou A.J. Data Science priorities for a University hospital-based instution of infectious disease: A viewpoint Clin. Infect: Dis.
Use of AI in Infectious disease. Agrebi S. et.al
Image Analysis and AI in Infectious disease diagnostics Smith. K.P et.al
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