ReviewScience (New York, N.Y.)2023
Leveraging artificial intelligence in the fight against infectious diseases.
Review in Science (New York, N.Y.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 138 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
138 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Development of siRNA therapeutics to combat microbial infections: a bibliometric analysis.Frontiers in cellular and infection microbiology · 2025Pooled it
- Artificial intelligence in early warning systems for infectious disease surveillance: a systematic review.Frontiers in public health · 2025Pooled it
- Antimicrobial resistance crisis: could artificial intelligence be the solution?Military Medical Research · 2024Pooled it
- Harnessing AI for advancing pathogenic microbiology: a bibliometric and topic modeling approach.Frontiers in microbiology · 2024Pooled it
- Artificial intelligence catalyzes antimicrobial peptide design.Synthetic and systems biotechnology · 2027Review
- Integrating mathematical modelling and artificial intelligence to combat emerging viral syndemics: A systematic review.New microbes and new infections · 2026Review
- Combating antimicrobial resistance through multimodal data via artificial intelligence.One health (Amsterdam, Netherlands) · 2026Review
- TACTIC: A transfer learning framework to predict drug interactions in emerging pathogens.Cell reports methods · 2026Article
- Artificial Intelligence-Guided Phenotypic Drug Repurposing Against Streptococcus pneumoniae.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Nucleic acid aptamers: new methods for selection, target validation, molecular diagnostics and therapeutics.Signal transduction and targeted therapy · 2026Review
- Design of a cyclic peptide targeting intracellular Staphylococcus aureus.Molecular biomedicine · 2026Article
- Deep-learning-based virtual screening of antibacterial compounds.Nature biotechnology · 2026Article
- A novel penicillin-binding protein inhibitor with unprecedented intracellular activity eradicates multiple pathogenic bacteria.PLoS pathogens · 2026Article
- Deep learning speeds the search for new antibiotic scaffolds.Nature biotechnology · 2026Article
- Integration of Federated Learning and Blockchain in Health Care: Tutorial on Medical Data, Architectures, Privacy, Security, and Regulatory Compliance.Journal of medical Internet research · 2026Article
- Goat gut microbiome as a reservoir for microorganism-encoded short peptides: regulation by host development age and nematode challenge.NPJ biofilms and microbiomes · 2026Article
- Advances in mosquito-borne disease surveillance using machine learning.New microbes and new infections · 2026Article
- Explainable machine learning differentiates necrotizing fasciitis and osteomyelitis via routine blood biomarkers.NPJ digital medicine · 2026Article
- Special Issue "Novel Mechanisms of Bacterial Antibiotic Resistance and Strategies to Fight Them".International journal of molecular sciences · 2026Article
- Antibiotic Mechanisms and Resistance: Molecular Insights and Therapeutic Strategies.Antibiotics (Basel, Switzerland) · 2026Review
78 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Despite advances in molecular biology, genetics, computation, and medicinal chemistry, infectious disease remains an ominous threat to public health. Addressing the challenges posed by pathogen outbreaks, pandemics, and antimicrobial resistance will require concerted interdisciplinary efforts. In conjunction with systems and synthetic biology, artificial intelligence (AI) is now leading to rapid progress, expanding anti-infective drug discovery, enhancing our understanding of infection biology, and accelerating the development of diagnostics. In this Review, we discuss approaches for detecting, treating, and understanding infectious diseases, underscoring the progress supported by AI in each case. We suggest future applications of AI and how it might be harnessed to help control infectious disease outbreaks and pandemics.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.