Applications of Artificial Intelligence in Microbial Diagnosis DOI Open Access
Yogendra Shelke, Ankit Badge, Nandkishor Bankar

и другие.

Cureus, Год журнала: 2023, Номер unknown

Опубликована: Ноя. 24, 2023

The diagnosis is an important factor in healthcare care, and it essential to identify microorganisms that cause infections diseases. application of artificial intelligence (AI) systems can improve disease management, drug development, antibiotic resistance prediction, epidemiological monitoring the field microbial diagnosis. AI quickly accurately detect infections, including new drug-resistant strains, enable early detection improved diagnostic techniques. bacterial focuses on speed, precision, identification pathogens ability predict resistance.

Язык: Английский

Origin of Antibiotics and Antibiotic Resistance, and Their Impacts on Drug Development: A Narrative Review DOI Creative Commons
Ghazala Muteeb, Md Tabish Rehman, Moyad Shahwan

и другие.

Pharmaceuticals, Год журнала: 2023, Номер 16(11), С. 1615 - 1615

Опубликована: Ноя. 15, 2023

Antibiotics have revolutionized medicine, saving countless lives since their discovery in the early 20th century. However, origin of antibiotics is now overshadowed by alarming rise antibiotic resistance. This global crisis stems from relentless adaptability microorganisms, driven misuse and overuse antibiotics. article explores subsequent emergence It delves into mechanisms employed bacteria to develop resistance, highlighting dire consequences drug including compromised patient care, increased mortality rates, escalating healthcare costs. The elucidates latest strategies against drug-resistant encompassing innovative approaches such as phage therapy, CRISPR-Cas9 technology, exploration natural compounds. Moreover, it examines profound impact resistance on development, rendering pursuit new economically challenging. limitations challenges developing novel are discussed, along with hurdles regulatory process that hinder progress this critical field. Proposals for modifying facilitate development presented. withdrawal major pharmaceutical firms research examined, potential re-engage interest. also outlines initiatives overcome economic incentivize emphasizing international collaborations partnerships. Finally, sheds light government-led a specific focus Middle East. discusses proactive measures taken governments region, Saudi Arabia United Arab Emirates, combat threat. In face multifaceted approach imperative. provides valuable insights complex landscape challenges, collaborative efforts required ensure future where remain effective tools safeguarding public health.

Язык: Английский

Процитировано

320

Antimicrobial resistance: Impacts, challenges, and future prospects DOI Creative Commons
Sirwan Khalid Ahmed, Safin Hussein, Karzan Qurbani

и другие.

Journal of Medicine Surgery and Public Health, Год журнала: 2024, Номер 2, С. 100081 - 100081

Опубликована: Март 2, 2024

Antimicrobial resistance (AMR) is a critical global health issue driven by antibiotic misuse and overuse in various sectors, leading to the emergence of resistant microorganisms. The history AMR dates back discovery penicillin, with rise multidrug-resistant pathogens posing significant challenges healthcare systems worldwide. antibiotics human animal health, as well agriculture, contributes spread genes, creating "Silent Pandemic" that could surpass other causes mortality 2050. affects both humans animals, treating infections. Various mechanisms, such enzymatic modification biofilm formation, enable microbes withstand effects antibiotics. lack effective threatens routine medical procedures lead millions deaths annually if left unchecked. economic impact substantial, projected losses trillions dollars financial burdens on agriculture. Artificial intelligence being explored tool combat improving diagnostics treatment strategies, although data quality algorithmic biases exist. To address effectively, One Health approach considers human, animal, environmental factors crucial. This includes enhancing surveillance systems, promoting stewardship programs, investing research development for new antimicrobial options. Public awareness, education, international collaboration are essential combating preserving efficacy future generations.

Язык: Английский

Процитировано

239

Knowledge, attitude, and practice of artificial intelligence among doctors and medical students in Syria: A cross-sectional online survey DOI Creative Commons
Sarya Swed, Hidar Alibrahim,

Nashaat Kamal Hamdy Elkalagi

и другие.

Frontiers in Artificial Intelligence, Год журнала: 2022, Номер 5

Опубликована: Сен. 29, 2022

Artificial intelligence has been prevalent recently as its use in the medical field is noticed to be increased. However, middle east countries like Syria are deficient multiple AI implementation methods of medicine. So, holding these necessary, which may incredibly beneficial for making diagnosis more accessible and help treatment. This paper intends determine AI's knowledge, attitude, practice among doctors students Syria. A questionnaire conducted an online cross-sectional study on google form website consisting demographic data, perception AI. There were 1,494 responses from both students. We included Syrian who currently residing Of participants, 255 (16.9%) doctors, while other 1,252 (83.1%) undergraduate About 1,055 (70%) participants have previous knowledge about only 357 (23.7%) know application field. Most shown positive attitudes toward necessity field; 689 (45.7%) individuals strongly agree, 628 (41.7%) agree. The had 3.327 times adequate than first year. In contrast, 6th-year 2.868 attitude higher residents assistant professors 2.371 4.422 students, respectively. Although most physicians do not sufficiently understand significance field, they favorable views regarding using authorities international organizations should suggest including artificial particularly when training fellowship physicians.

Язык: Английский

Процитировано

87

Artificial Intelligence for Antimicrobial Resistance Prediction: Challenges and Opportunities towards Practical Implementation DOI Creative Commons
Tabish Ali, Sarfaraz Ahmed, Muhammad Aslam

и другие.

Antibiotics, Год журнала: 2023, Номер 12(3), С. 523 - 523

Опубликована: Март 6, 2023

Antimicrobial resistance (AMR) is emerging as a potential threat to many lives worldwide. It very important understand and apply effective strategies counter the impact of AMR its mutation from medical treatment point view. The intersection artificial intelligence (AI), especially deep learning/machine learning, has led new direction in antimicrobial identification. Furthermore, presently, availability huge amounts data multiple sources made it more use these techniques identify interesting insights into genes such genes, mutations, drug identification, conditions favorable spread, so on. Therefore, this paper presents review state-of-the-art challenges opportunities. These include input features posing use, deep-learning/machine-learning models for robustness high accuracy, challenges, prospects practical purposes. concludes with encouragement AI sector intention diagnosis treatment, since presently most studies are at early stages minimal application practice disease.

Язык: Английский

Процитировано

78

Plant-Derived Antimicrobials and Their Crucial Role in Combating Antimicrobial Resistance DOI Creative Commons
Paola Angelini

Antibiotics, Год журнала: 2024, Номер 13(8), С. 746 - 746

Опубликована: Авг. 9, 2024

Antibiotic resistance emerged shortly after the discovery of first antibiotic and has remained a critical public health issue ever since. Managing in clinical settings continues to be challenging, particularly with rise superbugs, or bacteria resistant multiple antibiotics, known as multidrug-resistant (MDR) bacteria. This rapid development compelled researchers continuously seek new antimicrobial agents curb resistance, despite shrinking pipeline drugs. Recently, focus shifted plants, fungi, lichens, endophytes, various marine sources, such seaweeds, corals, other microorganisms, due their promising properties. For this review, an extensive search was conducted across scientific databases, including PubMed, Elsevier, ResearchGate, Scopus, Google Scholar, encompassing publications from 1929 2024. review provides concise overview mechanisms employed by develop followed in-depth exploration plant secondary metabolites potential solution MDR pathogens. In recent years, interest plant-based medicines surged, driven advantageous However, additional research is essential fully understand action verify safety phytochemicals. Future prospects for enhancing use combating antibiotic-resistant pathogens will also discussed.

Язык: Английский

Процитировано

29

The potential application of artificial intelligence in veterinary clinical practice and biomedical research DOI Creative Commons
Olalekan Chris Akinsulie, Ibrahim Idris, Victor Ayodele Aliyu

и другие.

Frontiers in Veterinary Science, Год журнала: 2024, Номер 11

Опубликована: Янв. 31, 2024

Artificial intelligence (AI) is a fast-paced technological advancement in terms of its application to various fields science and technology. In particular, AI has the potential play roles veterinary clinical practice, enhancing way care delivered, improving outcomes for animals ultimately humans. Also, recent years, emergence led new direction biomedical research, especially translational research with great potential, promising revolutionize science. applicable antimicrobial resistance (AMR) cancer drug design vaccine development, epidemiology, disease surveillance, genomics. Here, we highlighted discussed impact aspects practice proposing this technology as key tool addressing pressing global health challenges across domains.

Язык: Английский

Процитировано

24

Brave New World of Artificial Intelligence: Its Use in Antimicrobial Stewardship—A Systematic Review DOI Creative Commons

Rafaela Pinto-de-Sá,

Bernardo Sousa‐Pinto, Sofia Costa‐de‐Oliveira

и другие.

Antibiotics, Год журнала: 2024, Номер 13(4), С. 307 - 307

Опубликована: Март 28, 2024

Antimicrobial resistance (AMR) is a growing public health problem in the One Health dimension. Artificial intelligence (AI) emerging healthcare, since it helpful to deal with large amounts of data and as prediction tool. This systematic review explores use AI antimicrobial stewardship programs (ASPs) summarizes predictive performance machine learning (ML) algorithms, compared clinical decisions, inpatients outpatients who need prescriptions. includes eighteen observational studies from PubMed, Scopus, Web Science. The exclusion criteria comprised conducted only vitro, not addressing infectious diseases, or referencing models predictors. Data such study type, year publication, number patients, objective, ML algorithms used, features, predictors were extracted included publications. All concluded that useful assist teams multiple tasks identifying inappropriate prescribing practices, choosing appropriate antibiotic therapy, predicting AMR. most metric was AUC, which ranged 0.64 0.992. Despite risks ethical concerns raises, can play positive promising role ASP.

Язык: Английский

Процитировано

22

Mechanism of antibacterial resistance, strategies and next-generation antimicrobials to contain antimicrobial resistance: a review DOI Creative Commons
Wubetu Yihunie, Melese Getachew, Bantayehu Addis Tegegne

и другие.

Frontiers in Pharmacology, Год журнала: 2024, Номер 15

Опубликована: Авг. 16, 2024

Antibacterial drug resistance poses a significant challenge to modern healthcare systems, threatening our ability effectively treat bacterial infections. This review aims provide comprehensive overview of the types and mechanisms antibacterial resistance. To achieve this aim, thorough literature search was conducted identify key studies reviews on mechanisms, strategies next-generation antimicrobials contain antimicrobial In review, major with examples including target site modifications, decreased influx, increased efflux pumps, enzymatic inactivation antibacterials has been discussed. Moreover, biofilm formation, horizontal gene transfer methods also included. Furthermore, measures (interventions) taken control have discussed in detail. Overall, provides valuable insights into diverse employed by bacteria resist effects drugs, aim informing future research guiding stewardship efforts.

Язык: Английский

Процитировано

21

Challenges and applications of artificial intelligence in infectious diseases and antimicrobial resistance DOI Creative Commons
Angela Cesaro, Samuel C. Hoffman, Payel Das

и другие.

npj Antimicrobials and Resistance, Год журнала: 2025, Номер 3(1)

Опубликована: Янв. 7, 2025

Artificial intelligence (AI) has transformed infectious disease control, enhancing rapid diagnosis and antibiotic discovery. While conventional tests delay diagnosis, AI-driven methods like machine learning deep assist in pathogen detection, resistance prediction, drug These tools improve stewardship identify effective compounds such as antimicrobial peptides small molecules. This review explores AI applications diagnostics, therapy, discovery, emphasizing both strengths areas needing improvement.

Язык: Английский

Процитировано

9

Use of Biomaterials in 3D Printing as a Solution to Microbial Infections in Arthroplasty and Osseous Reconstruction DOI Creative Commons
Argyrios Periferakis, Aristodemos-Theodoros Periferakis, Lamprini Troumpata

и другие.

Biomimetics, Год журнала: 2024, Номер 9(3), С. 154 - 154

Опубликована: Март 1, 2024

The incidence of microbial infections in orthopedic prosthetic surgeries is a perennial problem that increases morbidity and mortality, representing one the major complications such medical interventions. emergence novel technologies, especially 3D printing, represents promising avenue development for reducing risk eventualities. There are already host biomaterials, suitable being tested antimicrobial properties when they coated with bioactive compounds, as antibiotics, or combined hydrogels antioxidant properties, chitosan metal nanoparticles, among others. materials discussed context this paper comprise beta-tricalcium phosphate (β-TCP), biphasic calcium (BCP), hydroxyapatite, lithium disilicate glass, polyetheretherketone (PEEK), poly(propylene fumarate) (PPF), poly(trimethylene carbonate) (PTMC), zirconia. While recent research results promising, further required to address increasing antibiotic resistance exhibited by several common pathogens, potential fungal infections, toxicity some nanoparticles. Other solutions, like incorporation phytochemicals, should also be explored. Incorporating artificial intelligence (AI) certain implants use AI against bacterial might represent viable solutions these problems. Finally, there legal considerations associated biomaterials widespread which must taken into account.

Язык: Английский

Процитировано

17