Jul 2026· Sheng wu gong cheng xue bao = Chinese journal of biotechnology· Vol 42 7, pp.
2902-2926
· 0 citations
Medicine
TL;DR
This review systematically elaborates on the biomedical big data ecosystem that drives the AI revolution, including multi-omics data, phenotypic and clinical data, and literature-based knowledge data, and proposes key future directions, such as building equitable data ecosystems, developing interpretable AI models, and deepening interdisciplinary collaborations.
Antimicrobial resistance (AMR) has become one of the most urgent threats to global public health, with an estimated 4.95 million deaths associated with bacterial resistance in 2019 alone. Conventional approaches to antibiotic development, resistance detection, and treatment selection are increasingly unable to keep pac...
Mia Carter, Brady Wilson· Journal of Public Health and...· 0 citations
This review discusses how AI can accelerate computational drug discovery, virtual screening (VS), and the repurposing of already-approved medications, and it can also optimize combination therapies through computational simulation.
D. Bhagwat, Sonali A. Chikhalwale, S. Mali et al.· Current pharmaceutical desig...· 0 citations
Antimicrobial resistance (AMR) poses a critical global health challenge, leading to substantial mortality and economic losses without science-based interventions. Conventional approaches to combating AMR have important limitations in addressing this escalating threat. Recent advances in AI, including deep learning, lar...
Qiu-Hua Xia, Jia-Yang Li, Wen-Qi Wu et al.· One Health· 0 citations
AI can certainly strengthen the global AMR response by complementing key areas of AMR such as antimicrobial stewardship, infection prevention, laboratory diagnostics, and global surveillance.
Tahani Alkalaf, E. Eker, O. Albarri et al.· Le infezioni in medicina· 0 citations
Bacterial infectious diseases remain a formidable global health challenge, exacerbated by the relentless rise of antimicrobial resistance (AMR) and the emergence of novel pathogens. Artificial intelligence (AI), encompassing machine learning (ML), deep learning (DL), and natural language processing (NLP), has emerged a...
Sarah Mitchell, James Patterson, Emily Davidson et al.· Journal of Public Health and...· 0 citations
This evidence-based literature review critically examines the evolution and application of computational technologies across the pharmaceutical pipeline, ranging from early expert systems like DENDRAL, computer-aided drug design (CADD), and quantitative structure-activity relationship (QSAR) modeling to AlphaFold 3 bio...
Leonardo Mairene Muniz· Brazilian Journal of Health...· 0 citations
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