Artificial Intelligence in Infectious Disease Detection and Control: A Systematic Literature Review of Advancements, Challenges, and Future Directions

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Systematic review highlights AI's role in outbreak prediction and real-time surveillance for infectious diseases.

AI models significantly enhance early detection and forecasting of infectious diseases, improving public health outcomes.
Literature review of 30 studies shows AI-based methods surpass traditional approaches in predictive accuracy and response speed.
Assessment included studies on machine learning, deep learning, and neural networks applied to infectious disease management.
Integration of AI tools into health infrastructures is essential, addressing challenges like data standardization and ethical concerns.

Abdul Wajid Fazil (2025) studied this question.

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View Full Paper

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Authors

Systematic review highlights AI's role in outbreak prediction and real-time surveillance for infectious diseases.

AI models significantly enhance early detection and forecasting of infectious diseases, improving public health outcomes.
Literature review of 30 studies shows AI-based methods surpass traditional approaches in predictive accuracy and response speed.
Assessment included studies on machine learning, deep learning, and neural networks applied to infectious disease management.
Integration of AI tools into health infrastructures is essential, addressing challenges like data standardization and ethical concerns.

Abdul Wajid Fazil (2025) studied this question.

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Bookmark