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Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates

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 chall...

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Autores principales: Rabaan, Ali A., Alhumaid, Saad, Mutair, Abbas Al, Garout, Mohammed, Abulhamayel, Yem, Halwani, Muhammad A., Alestad, Jeehan H., Bshabshe, Ali Al, Sulaiman, Tarek, AlFonaisan, Meshal K., Almusawi, Tariq, Albayat, Hawra, Alsaeed, Mohammed, Alfaresi, Mubarak, Alotaibi, Sultan, Alhashem, Yousef N., Temsah, Mohamad-Hani, Ali, Urooj, Ahmed, Naveed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9220767/
https://www.ncbi.nlm.nih.gov/pubmed/35740190
http://dx.doi.org/10.3390/antibiotics11060784
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author Rabaan, Ali A.
Alhumaid, Saad
Mutair, Abbas Al
Garout, Mohammed
Abulhamayel, Yem
Halwani, Muhammad A.
Alestad, Jeehan H.
Bshabshe, Ali Al
Sulaiman, Tarek
AlFonaisan, Meshal K.
Almusawi, Tariq
Albayat, Hawra
Alsaeed, Mohammed
Alfaresi, Mubarak
Alotaibi, Sultan
Alhashem, Yousef N.
Temsah, Mohamad-Hani
Ali, Urooj
Ahmed, Naveed
author_facet Rabaan, Ali A.
Alhumaid, Saad
Mutair, Abbas Al
Garout, Mohammed
Abulhamayel, Yem
Halwani, Muhammad A.
Alestad, Jeehan H.
Bshabshe, Ali Al
Sulaiman, Tarek
AlFonaisan, Meshal K.
Almusawi, Tariq
Albayat, Hawra
Alsaeed, Mohammed
Alfaresi, Mubarak
Alotaibi, Sultan
Alhashem, Yousef N.
Temsah, Mohamad-Hani
Ali, Urooj
Ahmed, Naveed
author_sort Rabaan, Ali A.
collection PubMed
description 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.
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spelling pubmed-92207672022-06-24 Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates Rabaan, Ali A. Alhumaid, Saad Mutair, Abbas Al Garout, Mohammed Abulhamayel, Yem Halwani, Muhammad A. Alestad, Jeehan H. Bshabshe, Ali Al Sulaiman, Tarek AlFonaisan, Meshal K. Almusawi, Tariq Albayat, Hawra Alsaeed, Mohammed Alfaresi, Mubarak Alotaibi, Sultan Alhashem, Yousef N. Temsah, Mohamad-Hani Ali, Urooj Ahmed, Naveed Antibiotics (Basel) Review 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. MDPI 2022-06-08 /pmc/articles/PMC9220767/ /pubmed/35740190 http://dx.doi.org/10.3390/antibiotics11060784 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Rabaan, Ali A.
Alhumaid, Saad
Mutair, Abbas Al
Garout, Mohammed
Abulhamayel, Yem
Halwani, Muhammad A.
Alestad, Jeehan H.
Bshabshe, Ali Al
Sulaiman, Tarek
AlFonaisan, Meshal K.
Almusawi, Tariq
Albayat, Hawra
Alsaeed, Mohammed
Alfaresi, Mubarak
Alotaibi, Sultan
Alhashem, Yousef N.
Temsah, Mohamad-Hani
Ali, Urooj
Ahmed, Naveed
Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates
title Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates
title_full Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates
title_fullStr Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates
title_full_unstemmed Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates
title_short Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates
title_sort application of artificial intelligence in combating high antimicrobial resistance rates
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9220767/
https://www.ncbi.nlm.nih.gov/pubmed/35740190
http://dx.doi.org/10.3390/antibiotics11060784
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