Leveraging artificial intelligence to combat antimicrobial resistance in geriatric care

Antimicrobial resistance (AMR) is a global issue affecting both humans and animals, causing severe public health and economic burdens. Multidrug resistance (MDR) has led to increased treatment failures and reduced effectiveness of antimicrobial agents. Global leaders have pledged to reduce AMR-related deaths by 10% annually by 2030. AMR presents acute challenges in geriatric healthcare, where multidrug-resistant organisms (MDROs) contribute to increased morbidity, mortality, and healthcare costs. Overuse and misuse of antimicrobials have accelerated the selection and proliferation of resistant strains. The global disparity in access to effective antibiotics exacerbates the AMR crisis. In 2021, an estimated 4.71 million deaths were associated with AMR, with 1.14 million directly attributable to AMR. The Global Research on Antimicrobial Resistance (GRAM) Project forecasts bacterial AMR will cause 39 million deaths between 2025 and 2050. Integrating AI into healthcare systems presents promising opportunities for addressing AMR challenges by facilitating tailored interventions, early threat detection, and real-time surveillance.