Artificial intelligence and infectious diseases: an evidence-driven conceptual framework for research, public health, and clinical practice

2025/09/17 by Anna Odone, Chiara Barbati, Silvia Amadasi +3 · 1 voice
Computer Science · Medicine · #Artificial Intelligence in Healthcare and Education #COVID-19 diagnosis using AI #Machine Learning in Healthcare

paper · doi:10.1016/s1473-3099(25)00412-8

openalex publication_date 2025/09/17 · crossref created 2025/09/17 · openalex created_date 2025/10/10 · crossref issued 2026/03/01 · crossref published 2026/03/01 · crossref published-print 2026/03/01 · crossref deposited 2026/03/02 · crossref indexed 2026/07/28 · openalex updated_date 2026/07/28

Citations

• Artificial intelligence: a modern approach
• COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images
• Highly accurate protein structure prediction with AlphaFold
• Infectious disease in an era of global change
• Evolutionary-scale prediction of atomic-level protein structure with a language model
• Machine learning in infectious diseases: potential applications and limitations
• Deep-learning-enabled antibiotic discovery through molecular de-extinction
• Using artificial intelligence to document the hidden RNA virosphere
• Artificial intelligence for modelling infectious disease epidemics
• Advances and Open Problems in Federated Learning

Discussions

• Artificial intelligence and infectious diseases: an evidencedriven conceptual framework for research, public health, and clinical practice Anna Odone, et al. Lancet Infect Dis, 2025 doi.org/10.1016/S1 [bsky, 0 points, 0 comments]