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Implications of Artificial Intelligence in Addressing Antimicrobial Resistance: Innovations, Global Challenges, and Healthcare's Future.
Branda, Francesco; Scarpa, Fabio.
Affiliation
  • Branda F; Unit of Medical Statistics and Molecular Epidemiology, Università Campus Bio-Medico di Roma, 00128 Rome, Italy.
  • Scarpa F; Department of Biomedical Sciences, University of Sassari, 07100 Sassari, Italy.
Antibiotics (Basel) ; 13(6)2024 May 29.
Article in En | MEDLINE | ID: mdl-38927169
ABSTRACT
Antibiotic resistance poses a significant threat to global public health due to complex interactions between bacterial genetic factors and external influences such as antibiotic misuse. Artificial intelligence (AI) offers innovative strategies to address this crisis. For example, AI can analyze genomic data to detect resistance markers early on, enabling early interventions. In addition, AI-powered decision support systems can optimize antibiotic use by recommending the most effective treatments based on patient data and local resistance patterns. AI can accelerate drug discovery by predicting the efficacy of new compounds and identifying potential antibacterial agents. Although progress has been made, challenges persist, including data quality, model interpretability, and real-world implementation. A multidisciplinary approach that integrates AI with other emerging technologies, such as synthetic biology and nanomedicine, could pave the way for effective prevention and mitigation of antimicrobial resistance, preserving the efficacy of antibiotics for future generations.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Antibiotics (Basel) Year: 2024 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Antibiotics (Basel) Year: 2024 Document type: Article Affiliation country: Country of publication: