Catheter-associated urinary tract infections: current challenges and future prospects

GT Werneburg - Research and reports in urology, 2022 - Taylor & Francis
Catheter-associated urinary tract infection (CAUTI) is the most common healthcare-
associated infection and cause of secondary bloodstream infections. Despite many …

Role of the microbiota in response to and recovery from cancer therapy

SJ Blake, Y Wolf, B Boursi, DJ Lynn - Nature Reviews Immunology, 2024 - nature.com
Our understanding of how the microbiota affects the balance between response to and
failure of cancer treatment by modulating the tumour microenvironment and systemic …

Antimicrobial resistance: a concise update

CS Ho, CTH Wong, TT Aung… - The Lancet …, 2024 - thelancet.com
Antimicrobial resistance (AMR) is a serious threat to global public health, with approximately
5 million deaths associated with bacterial AMR in 2019. Tackling AMR requires a …

Artificial intelligence and machine learning assisted drug delivery for effective treatment of infectious diseases

S He, LG Leanse, Y Feng - Advanced drug delivery reviews, 2021 - Elsevier
In the era of antimicrobial resistance, the prevalence of multidrug-resistant microorganisms
that resist conventional antibiotic treatment has steadily increased. Thus, it is now …

Applications of machine learning to the problem of antimicrobial resistance: an emerging model for translational research

MN Anahtar, JH Yang, S Kanjilal - Journal of clinical microbiology, 2021 - Am Soc Microbiol
Antimicrobial resistance (AMR) remains one of the most challenging phenomena of modern
medicine. Machine learning (ML) is a subfield of artificial intelligence that focuses on the …

Using machine learning to predict antimicrobial resistance―a literature review

A Sakagianni, C Koufopoulou, G Feretzakis, D Kalles… - Antibiotics, 2023 - mdpi.com
Machine learning (ML) algorithms are increasingly applied in medical research and in
healthcare, gradually improving clinical practice. Among various applications of these novel …

[HTML][HTML] High-resolution analyses of associations between medications, microbiome, and mortality in cancer patients

CL Nguyen, KA Markey, O Miltiadous, A Dai, N Waters… - Cell, 2023 - cell.com
Discerning the effect of pharmacological exposures on intestinal bacterial communities in
cancer patients is challenging. Here, we deconvoluted the relationship between drug …

Personalized antibiograms for machine learning driven antibiotic selection

CK Corbin, L Sung, A Chattopadhyay… - Communications …, 2022 - nature.com
Abstract Background The Centers for Disease Control and Prevention identify antibiotic
prescribing stewardship as the most important action to combat increasing antibiotic …

Antimicrobial resistance crisis: could artificial intelligence be the solution?

GY Liu, D Yu, MM Fan, X Zhang, ZY Jin, C Tang… - Military Medical …, 2024 - Springer
Antimicrobial resistance is a global public health threat, and the World Health Organization
(WHO) has announced a priority list of the most threatening pathogens against which novel …

From Data to Decisions: Leveraging Artificial Intelligence and Machine Learning in Combating Antimicrobial Resistance–a Comprehensive Review

JMP de la Lastra, SJT Wardell, T Pal… - Journal of medical …, 2024 - Springer
The emergence of drug-resistant bacteria poses a significant challenge to modern medicine.
In response, Artificial Intelligence (AI) and Machine Learning (ML) algorithms have emerged …