Machine learning (ML) algorithms are increasingly applied in medical research and in
healthcare, gradually improving clinical practice. Among various applications of these novel …

Introduction Antimicrobial resistance (AMR) is a global health threat; rapid and timely
identification of AMR improves patient prognosis and reduces inappropriate antibiotic use …

Objectives In the era of increasing antimicrobial resistance, the need for early identification
and prompt treatment of multi-drug-resistant infections is crucial for achieving favorable …

Purpose Artificial intelligence is part of our daily life and machine learning techniques offer
possibilities unknown until now in medicine. This study aims to offer an evaluation of the …

Hospital-acquired infections, particularly in ICU, are becoming more frequent in recent
years, with the most serious of them being Gram-negative bacterial infections. Among them …

Antimicrobials have paved the way for medical and social development over the last century
and are indispensable for treating infections in humans and animals. The dramatic spread …

Background/Objectives: The emergence of antimicrobial resistance (AMR) due to the misuse
and overuse of antibiotics has become a critical threat to global public health. There is a dire …

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which caused
coronavirus diseases (COVID-19) in late 2019 in China created a devastating economical …

Introduction Machine learning (ML) is increasingly being used to predict antimicrobial
resistance (AMR). This review aims to provide physicians with an overview of the literature …

Methicillin-resistant Staphylococcus aureus (MRSA) poses significant morbidity and
mortality in hospitals. Rapid, accurate risk stratification of MRSA is crucial for optimizing …