This paper investigates the applications of explainable AI (XAI) in healthcare, which aims to
provide transparency, fairness, accuracy, generality, and comprehensibility to the results …

Escherichia coli is one of the species most frequently involved in biofilm-related diseases,
being especially important in urinary tract infections, causing relapses or chronic infections …

Critical care practice has been embodied in the healthcare system since the
institutionalization of intensive care units (ICUs) in the late'50s. Over time, this sector has …

This study introduces a novel pruning approach based on explainable graph convolutional
networks, strategically amalgamating pruning and quantisation, aimed to tackle the …

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 …

Starting in 2008, the adoption of electronic health records (EHR) in US hospitals has grown
exponentially from 9% to 96% of hospitals, while also exhibiting substantial uptake in …

Objectives Diagnosis and management of intensive care unit (ICU)-acquired bloodstream
infections are often based on positive blood culture results. This retrospective cohort study …

Background Health care–associated infection (HAI) surveillance is vital for safety in health
care settings. It helps identify infection risk factors, enhancing patient safety and quality …

The aim of the study was to build a machine learning-based predictive model to discriminate
between hospitalized patients at low risk and high risk of bloodstream infection (BSI). A Data …

Pressure ulcers carry a significant risk in clinical practice. This paper proposes a practical
and interpretable approach to estimate the risk levels of pressure ulcers using decision tree …