Evidence map›Paper›PMID 35740190›Full record

ReviewAntibiotics (Basel, Switzerland)2022

Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates.

Ali A Rabaan, Saad Alhumaid, Abbas Al Mutair, Mohammed Garout, Yem Abulhamayel, Muhammad A Halwani, Jeehan H Alestad, Ali Al Bshabshe, Tarek Sulaiman, Meshal K AlFonaisan and 9 more

Abstract readReview
In one paragraph

Review in Antibiotics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

58 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Ali A RabaanMolecular Diagnostic Laboratory, Johns Hopkins Aramco Healthcare, Dhahran 31311, Saudi Arabia.
Saad AlhumaidAdministration of Pharmaceutical Care, Al-Ahsa Health Cluster, Ministry of Health, Al-Ahsa 31982, Saudi Arabia.ORCID 0000-0003-4552-4513
Abbas Al MutairResearch Center, Almoosa Specialist Hospital, Alhassa, Al-Ahsa 36342, Saudi Arabia.
Mohammed GaroutDepartment of Community Medicine and Health Care for Pilgrims, Faculty of Medicine, Umm Al-Qura University, Makkah 21955, Saudi Arabia.
Yem AbulhamayelSpecialty Internal Medicine Department, Johns Hopkins Aramco Healthcare, Dhahran 34465, Saudi Arabia.
Muhammad A HalwaniDepartment of Medical Microbiology, Faculty of Medicine, Al Baha University, Al Baha 4781, Saudi Arabia.
Jeehan H AlestadImmunology and Infectious Microbiology Department, University of Glasgow, Glasgow G1 1XQ, UK.
Ali Al BshabsheAdult Critical Care Department of Medicine, Division of Adult Critical Care, College of Medicine, King Khalid University, Abha 62561, Saudi Arabia.ORCID 0000-0003-0974-7226
Tarek SulaimanInfectious Diseases Section, Medical Specialties Department, King Fahad Medical City, Riyadh 12231, Saudi Arabia.
Meshal K AlFonaisanBasic Medical Sciences, Majmaah University, Majmaah 11952, Saudi Arabia.
Tariq AlmusawiInfectious Disease and Critical Care Medicine Department, Dr. Sulaiman Alhabib Medical Group, Alkhobar 34423, Saudi Arabia.
Hawra AlbayatInfectious Disease Department, King Saud Medical City, Riyadh 7790, Saudi Arabia.
Mohammed AlsaeedInfectious Disease Division, Department of Medicine, Prince Sultan Military Medical City, Riyadh 11159, Saudi Arabia.ORCID 0000-0002-0503-2154
Mubarak AlfaresiDepartment of Pathology and Laboratory Medicine, Sheikh Khalifa General Hospital, Umm Al Quwain 499, United Arab Emirates.ORCID 0000-0003-2523-835X
Sultan AlotaibiMolecular Microbiology Department, King Fahad Medical City, Riyadh 11525, Saudi Arabia.
Yousef N AlhashemDepartment of Clinical Laboratory Sciences, Mohammed AlMana College of Health Sciences, Dammam 34222, Saudi Arabia.ORCID 0000-0003-4435-3003
Mohamad-Hani TemsahPediatric Department, College of Medicine, King Saud University, Riyadh 11451, Saudi Arabia.ORCID 0000-0002-4389-9322
Urooj AliDepartment of Biotechnology, Faculty of Life Sciences, University of Central Punjab, Lahore 54000, Pakistan.ORCID 0000-0002-6640-752X
Naveed AhmedDepartment of Medical Microbiology and Parasitology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu 16150, Kelantan, Malaysia.ORCID 0000-0003-1504-1705

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

advancesAMRantibiotic stewardshipbetter diagnosisdiagnostic microbiologyglobal platform

Identifiers

PMID35740190
PMCPMC9220767

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.