SynthesisMilitary Medical Research2024
Antimicrobial resistance crisis: could artificial intelligence be the solution?
Synthesis in Military Medical Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 1 of them a synthesis 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
52 citing papers in PubMed, 1 synthesis or guideline pooled it, 86 citations in OpenAlex.
- Global insights into MRSA bacteremia: a bibliometric analysis and future outlook.Frontiers in microbiology · 2024Pooled it
- Combating antimicrobial resistance through multimodal data via artificial intelligence.One health (Amsterdam, Netherlands) · 2026Review
- Development and Biological Evaluation of FL18-Based Novel Antimicrobial Peptide Constructs Against Bacterial Pathogens.ACS omega · 2026Article
- Recent advancements in artificial intelligence applications for the mitigation of antimicrobial resistance: challenges and opportunities.JAC-antimicrobial resistance · 2026Review
- KEGG orthology-based machine learning reveals functional determinants of antimicrobial resistance inMicrobiology spectrum · 2026Article
- Engineering host‑defense peptides enhanced by artificial intelligence and nano delivery systems to overcome biofilms and antimicrobial resistance.Engineering microbiology · 2026Review
- AI-Driven Plant-Derived Anti-Infectives: Integrating Traditional Wisdom into Precision Medicine Against AMR.Life (Basel, Switzerland) · 2026Review
- Mapping 25 years of research on gut microbiota and antibiotic resistance: bibliometric insights and future directions.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026Review
- AI-Powered Microscopic Diagnostic Techniques forJournal of dentistry (Shiraz, Iran) · 2026Article
- Performance of predictive AI-based clinical decision support systems across clinical domains: A systematic review and meta-analysis.PLOS digital health · 2026Article
- Review
- The Application of artificial intelligence in periprosthetic joint infection.Journal of advanced research · 2026Review
- Burden of antimicrobial resistance in the WHO Southeast Asia and Western Pacific Regions, 1990-2021: a cross-country systematic analysis with forecasts to 2050.Military Medical Research · 2026Article
- From drug export to envelope fitness: characterizing the regulatory landscape of selectiveFrontiers in microbiology · 2026Article
- Advances in phage therapy forFrontiers in microbiology · 2026Review
- Bacteriophage therapy beyond antibiotics: emerging innovations for infectious and non-infectious diseases.Frontiers in cellular and infection microbiology · 2026Review
- A comprehensive review on bacterial endophytic secondary metabolites: a road map from crude extract to lead molecule production.Frontiers in pharmacology · 2026Review
- Antimicrobial Resistance: The Answers.British journal of biomedical science · 2026Review
- Uncloaking the black-box: the need for explainable artificial intelligence in clinical microbiology and infectious diseases applications.Frontiers in public health · 2026Review
- A roadmap for medical large language models: a review of foundations, applications, and challenges.Military Medical Research · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 6 institutions in 3 countries.
Funding
Abstract
Antimicrobial resistance is a global public health threat, and the World Health Organization (WHO) has announced a priority list of the most threatening pathogens against which novel antibiotics need to be developed. The discovery and introduction of novel antibiotics are time-consuming and expensive. According to WHO's report of antibacterial agents in clinical development, only 18 novel antibiotics have been approved since 2014. Therefore, novel antibiotics are critically needed. Artificial intelligence (AI) has been rapidly applied to drug development since its recent technical breakthrough and has dramatically improved the efficiency of the discovery of novel antibiotics. Here, we first summarized recently marketed novel antibiotics, and antibiotic candidates in clinical development. In addition, we systematically reviewed the involvement of AI in antibacterial drug development and utilization, including small molecules, antimicrobial peptides, phage therapy, essential oils, as well as resistance mechanism prediction, and antibiotic stewardship.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.