Clinical Diagnostics of Bacterial Infections and Their Resistance to Antibiotics—Current State and Whole Genome Sequencing Implementation Perspectives
Antimicrobial resistance (AMR), defined as the ability of microorganisms to withstand
antimicrobial treatment, is responsible for millions of deaths annually. The rapid spread of …
antimicrobial treatment, is responsible for millions of deaths annually. The rapid spread of …
Artificial intelligence: A promising tool for application in phytopathology
VE González-Rodríguez, I Izquierdo-Bueno… - Horticulturae, 2024 - mdpi.com
Artificial intelligence (AI) is revolutionizing approaches in plant disease management and
phytopathological research. This review analyzes current applications and future directions …
phytopathological research. This review analyzes current applications and future directions …
Short turnaround time of seven to nine hours from sample collection until informed decision for sepsis treatment using nanopore sequencing
Bloodstream infections (BSIs) and sepsis are major health problems, annually claiming
millions of lives. Traditional blood culture techniques, employed to identify sepsis-causing …
millions of lives. Traditional blood culture techniques, employed to identify sepsis-causing …
Integrating whole genome sequencing and machine learning for predicting antimicrobial resistance in critical pathogens: a systematic review of antimicrobial …
Background Infections caused by antibiotic-resistant bacteria pose a major challenge to
modern healthcare. This systematic review evaluates the efficacy of machine learning (ML) …
modern healthcare. This systematic review evaluates the efficacy of machine learning (ML) …
Machine learning-assisted image-based optical devices for health monitoring and food safety
M Mousavizadegan, F Shalileh… - TrAC Trends in …, 2024 - Elsevier
The advent of artificial intelligence has highly impacted the process of image processing and
pattern recognition, hence influencing biomedical researchers to implement machine …
pattern recognition, hence influencing biomedical researchers to implement machine …
Tackling the Antimicrobial Resistance “Pandemic” with Machine Learning Tools: A Summary of Available Evidence
Antimicrobial resistance is recognised as one of the top threats healthcare is bound to face
in the future. There have been various attempts to preserve the efficacy of existing …
in the future. There have been various attempts to preserve the efficacy of existing …
Culture and amplification-free nanopore sequencing for rapid detection of pathogens and antimicrobial resistance genes from urine
AB Bellankimath, C Chapagain, S Branders… - European Journal of …, 2024 - Springer
Abstract Purpose Urinary Tract Infections (UTIs) are among the most prevalent infections
globally. Every year, approximately 150 million people are diagnosed with UTIs worldwide …
globally. Every year, approximately 150 million people are diagnosed with UTIs worldwide …
[PDF][PDF] Artificial Intelligence: A Promising Tool for Application in Phytopathology. Horticulturae 2024, 10, 197
VE González-Rodríguez, I Izquierdo-Bueno… - 2024 - academia.edu
Artificial intelligence (AI) is revolutionizing approaches in plant disease management and
phytopathological research. This review analyzes current applications and future directions …
phytopathological research. This review analyzes current applications and future directions …
DnnARs: An Artificial Intelligence Technique for Prediction of Antimicrobial Resistant Strains in E. coli Bacteria Causing Urine Tract Infection
DSK Nayak, A Priyadarshini, P Mahanta, T Das… - SN Computer …, 2024 - Springer
The rise of antimicrobial resistance (AMR) in bacteria that cause infectious diseases poses a
significant global health challenge, necessitating advanced prediction technology for …
significant global health challenge, necessitating advanced prediction technology for …
Hypothesis-Driven Deep Learning for Out of Distribution Detection
Predictions of opaque black-box systems are frequently deployed in high-stakes
applications such as healthcare. For such applications, it is crucial to assess how models …
applications such as healthcare. For such applications, it is crucial to assess how models …