Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates

Abstract

Artificial intelligence (AI) is a branch of science and engineering that focuses on the computational understanding of intelligent behavior. Many human professions, including clinical diagnosis and prognosis, are greatly useful from AI. Antimicrobial resistance (AMR) is among the most critical challenges facing Pakistan and the rest of the world. The rising incidence of AMR has become a significant issue, and authorities must take measures to combat the overuse and incorrect use of antibiotics in order to combat rising resistance rates. The widespread use of antibiotics in clinical practice has not only resulted in drug resistance but has also increased the threat of super-resistant bacteria emergence. As AMR rises, clinicians find it more difficult to treat many bacterial infections in a timely manner, and therapy becomes prohibitively costly for patients. To combat the rise in AMR rates, it is critical to implement an institutional antibiotic stewardship program that monitors correct antibiotic use, controls antibiotics, and generates antibiograms. Furthermore, these types of tools may aid in the treatment of patients in the event of a medical emergency in which a physician is unable to wait for bacterial culture results. AI’s applications in healthcare might be unlimited, reducing the time it takes to discover new antimicrobial drugs, improving diagnostic and treatment accuracy, and lowering expenses at the same time. The majority of suggested AI solutions for AMR are meant to supplement rather than replace a doctor’s prescription or opinion, but rather to serve as a valuable tool for making their work easier. When it comes to infectious diseases, AI has the potential to be a game-changer in the battle against antibiotic resistance. Finally, when selecting antibiotic therapy for infections, data from local antibiotic stewardship programs are critical to ensuring that these bacteria are treated quickly and effectively. Furthermore, organizations such as the World Health Organization (WHO) have underlined the necessity of selecting the appropriate antibiotic and treating for the shortest time feasible to minimize the spread of resistant and invasive resistant bacterial strains.

Knowledge, attitude, and practice of artificial intelligence among doctors and medical students in Syria: A cross-sectional online survey

“…better understand AI algorithms (Rabaan et al, 2022). There were significant obstacles to integrating AI in the healthcare sector after the Syrian conflict, including the disintegration of healthcare services, the devastation of hospitals, the migration of healthcare staff, and the fall in medical education and training.…”

“…However, there are also unbelievable preconceptions of what AI is capable of and how the future of the healthcare sector will pan out, such as the assumption that AI will eventually replace doctors and that programming skills are required to use AI effectively. It was necessary to introduce AI in medical education because it can provide specific feedback to support learning and better understand AI algorithms (Rabaan et al, 2022 ). There were significant obstacles to integrating AI in the healthcare sector after the Syrian conflict, including the disintegration of healthcare services, the devastation of hospitals, the migration of healthcare staff, and the fall in medical education and training.…”

Prevalence of Bacterial Pathogens among Symptomatic–SARS-CoV-2 PCR-Negative Patients

“…It is crucial to utilize the right antibiotics in order to improve patient care, minimize costs, and decrease the duration of hospital stay and emotional burden on families, especially in resource-limited settings. Prior to receiving culture reports, which contain precise information regarding the pattern of antibiotic susceptibility of the suspected organism, patients who are critically ill begin treatments based on antibiograms [ 18 ]. Since culture reports take almost 48 h, sometimes based on the conditions of patients, the clinicians cannot wait for the reports, which is why they start treatment based on institutional antibiograms [ 18 ].…”

Knowledge Mapping of Nigeria’s Scientific Contribution to Antimicrobial Resistance Research: A visualized investigation using VOS viewer and Cite Space

“…It is pertinent to boost research in all thematic areas of AMR research in the country to significantly facilitate processes that will slow down the spread of AMR in the country. Research themes exploring the use of molecular and AI systems for AMR detection, surveillance, and drug discovery must be enhanced to confront rising bacterial resistance by significantly reducing the time taken to find new antimicrobials, improving diagnostic and treatment precision, as well as lowering costs [30]. A hotspot is a scientific topic of discussion in a series of documents which are inextricably connected to a particular time period [31].…”