Latest AI and machine learning research in critical care for healthcare professionals.
The prediction of nanoparticles (NPs) distribution is crucial for the diagnosis and treatment of t...
This study reports the findings of qualitative interview sessions conducted with ICU clinicians fo...
Patient-ventilator asynchrony (PVA) is a common and critical issue during mechanical ventilation, ...
Acute brain dysfunction (ABD) is a common, severe ICU complication, presenting as delirium or coma...
Automatic medical report generation supports clinical diagnosis, reduces the workload of radiologi...
While previous multimodal slow-thinking methods have demonstrated remarkable success in single-ima...
Septic acute respiratory distress syndrome (ARDS) is a complex and noteworthy type, but its molecula...
Individual treatment effect (ITE) estimation is to evaluate the causal effects of treatment strate...
Around 10% of newborns require some help to initiate breathing, and 5\% need ventilation assistanc...
Multi-omics data often suffer from the "big $p$, small $n$" problem where the dimensionality of feat...
The issue of failed weaning is a critical concern in the intensive care unit (ICU) setting. This s...
Hypertensive retinopathy (HR) is a severe eye disease that may cause permanent vision loss if not ...
In biomedical research and other fields, it is now common to generate high content data that are b...
The multivariate, asynchronous nature of real-world clinical data, such as that generated in Inten...
Next-generation mixed-criticality Systems-on-chip (SoCs) for robotics, automotive, and space must ...
Background: The search for new biomarkers that allow an early diagnosis in sepsis has become a nec...
This paper introduces Multi-Modal Retrieval-Augmented Generation (M^2RAG), a benchmark designed to...
In low-income and resource-limited countries, distinguishing COVID-19 from other respiratory disease...
Heart failure is one of the leading causes of death worldwide, with millons of deaths each year, a...
In critical care settings, where precise and timely interventions are crucial for health outcomes,...
Multi-modal Large Language Models (MLLMs) are capable of precisely extracting high-level semantic ...