Role of Artificial Intelligence in Fighting Antimicrobial Resistance in Pediatrics

Abstract

Artificial intelligence (AI) is a field of science and engineering concerned with the computational understanding of what is commonly called intelligent behavior. AI is extremely useful in many human activities including medicine. The aim of our narrative review is to show the potential role of AI in fighting antimicrobial resistance in pediatric patients. We searched for PubMed articles published from April 2010 to April 2020 containing the keywords “artificial intelligence”, “machine learning”, “antimicrobial resistance”, “antimicrobial stewardship”, “pediatric”, and “children”, and we described the different strategies for the application of AI in these fields. Literature analysis showed that the applications of AI in health care are potentially endless, contributing to a reduction in the development time of new antimicrobial agents, greater diagnostic and therapeutic appropriateness, and, simultaneously, a reduction in costs. Most of the proposed AI solutions for medicine are not intended to replace the doctor’s opinion or expertise, but to provide a useful tool for easing their work. Considering pediatric infectious diseases, AI could play a primary role in fighting antibiotic resistance. In the pediatric field, a greater willingness to invest in this field could help antimicrobial stewardship reach levels of effectiveness that were unthinkable a few years ago.

Retrospective 8-Year Study on the Antibiotic Resistance of Uropathogens in Children Hospitalised for Urinary Tract Infection in the Emilia-Romagna Region, Italy

“…Unfortunately, a great number of these antibiotic prescriptions are unnecessary or inappropriate, as shown by the evidence that these drugs are frequently given to children who do not have bacterial diseases or an infectious disease [30,31]. The high prevalence of amoxicillin-clavulanate resistance can be explained by the reported high prescription rate of this drug in children with common respiratory infections (i.e., pharyngotonsillitis and acute otitis media) in the Emilia-Romagna Region [32] and highlights the importance of antimicrobial stewardship projects for a more rational use of this drug [33,34].…”

Gut Microbiota and Obesity in Adults and Children: The State of the Art

“…Antibiotics are the most prescribed and administered drug during infancy, due to the natural propensity of children to come into contact with new pathogens in order to develop their immune systems, some of them indirectly taken during intrauterine life (i.e., prophylaxis of vaginal group B Streptococcus and cesarean section delivery) or to prevent or treat bacterial infections typical of preterm infants ( 17 , 52 ). However, they must be administered judiciously for two reasons that both have a tremendous impact on public health: first, to delay or better stop the widespread problem of antibiotic resistance; second, because of their side effects that occur by acting also on the symbiotic bacteria of the human organism, including the gut microbiota ( 53 ). In 2014, Azad et al reported significantly greater odds of childhood overweight at age 9 and 12 years in boys exposed to antibiotics during the first year of life regardless of the drug dose and the number of courses, even after adjusting for relevant covariates (birth weight, family income, child, and maternal asthma) and measures of child diet and physical activity ( 54 ).…”

Extensive validation and prospective observation of the impact of an AI-based rapid antibiotics susceptibility prediction platform in multiple medical centers

“…Generally, integrating larger amounts of data (laboratory, clinical, geographical) is needed to validate a medical AI. 22 Specifically, external validation or independent testing for a medical AI estimates the robustness of a medical AI in a variety of institutes. To examine the robustness of XBugHunter, we conducted internal validation (Figure 3 this basis, we deployed XBugHunter in our routine practice to predict susceptibility results for S. aureus and A. baumannii.…”