Artificial Intelligence in Infectious Diseases: From Pathogen Recognition to Personalized Medicine
A special issue of Pathogens (ISSN 2076-0817).
Deadline for manuscript submissions: 20 February 2026 | Viewed by 37
Special Issue Editors
Interests: host/pathogen interactions; T-cell response; serology; respiratory infections; inflammation; immune monitoring
Interests: healthy ageing; bioinformatics; biostatistics; epidemiology; influenza; infectious diseases; deep learning; machine; public health
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) is revolutionizing the management of infectious diseases by bridging pathogen detection and personalized treatment strategies. Advanced machine learning models excel in analyzing vast datasets, enabling rapid identification of pathogens through genomic sequencing or imaging. For instance, AI-powered algorithms can detect subtle patterns in microscopy images or predict viral mutations, accelerating diagnostics and outbreak tracking.
Beyond pathogen recognition, AI enhances disease surveillance by integrating real-time data from global health databases, social media, and environmental sensors to forecast epidemics. During the COVID-19 pandemic, AI models predicted viral spread and optimized resource allocation, demonstrating their public health utility.
In personalized medicine, AI tailors therapies to individual patients by analyzing patient-specific factors such as genetics, immune responses, and comorbidities. Predictive models identify high-risk individuals and recommend targeted interventions, while AI-driven drug discovery platforms streamline the development of novel antivirals or vaccines.
However, challenges like data privacy, algorithmic bias, and model interpretability require rigorous oversight. Collaborative efforts among clinicians, data scientists, and policymakers are essential to harness AI’s full potential ethically. As AI evolves, it promises a paradigm shift—transforming infectious disease management from reactive to proactive, and ultimately, delivering precision care for global populations.
This Special Issue covers the following topics:
- AI approaches for predicting host–pathogen interactions at the molecular level;
- Tools for predicting disease severity and patient outcomes;
- Machine learning for faster and more accurate infectious disease diagnostics;
- AI applications in vaccine design, development, and monitoring.
Dr. Giorgio Fedele
Dr. Annapina Palmieri
Guest Editors
Manuscript Submission Information
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Keywords
- machine learning
- infectious disease
- artificial intelligence
- immune responses
- host-pathogen interactions
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