Antimicrobial resistance crisis: could artificial intelligence be the solution?

Journal article

 The computational comprehension of intelligent behavior is the main goal of the scientific and engineering field of artificial intelligence (AI). Many human professions, particularly clinical diagnosis and prognosis, greatly benefit from artificial intelligence. The authorities need to take action to stop the excessive and improper the application of antibiotics to battle the increasing percentages of resistance to antibiotics since the occurrence of AMR is becoming a serious problem. In addition to causing drug resistance, the extensive using antibiotics in medical settings has raised the risk of super-resistant microorganisms. As antimicrobial resistance (AMR) increases, physicians face challenges in rapidly treating bacterial infections, and the expense of medicine may become unaffordable for patients\u27 healthcare needs. Potential benefits include a potentially infinite speed up in the development of novel antimicrobial medications, increased precision in diagnosis and treatment, and decreased costs all at the same time, the WHO, has released a ranking of the most important dangerous infections that require the development of novel antibiotics due to the threat posed by antimicrobial resistance to global public health. The search and introduction of novel antibiotics is an expensive and time-consuming procedure. Just eighteen new antibiotics have been authorized since 2014, In line with the WHO study on clinically developed antibacterial medications. Thus, new antibiotics are desperately needed. Since its latest technological advancement, artificial intelligence (AI) has been quickly used in medication research, significantly increasing the effectiveness of discovering new antibiotics. Most AI solutions for AMR that have been proposed are designed to be useful tools to assist doctors in their work, not to take the place of a doctor\u27s prescription or advice

Authors: Liu, G-Y; Yu, D; Fan, M-M; Zhang, X; Jin, Z-Y

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: KeAi Communications
• Journal: Military Medical Research
• Volume: 11
• Issue: 1
• Pages: 7-7
• Article number: 7
• Publication date: 2024-01-22
• DOI: 10.1186/s40779-024-00510-1
• EISSN: 2054-9369
• ISSN: 2054-9369
• Language: English
• Keywords: Resistance (ecology); Microbiology; Medicine; Antimicrobial; Biology