Latest AI and machine learning research in critical care for healthcare professionals.
BackgroundIntensive care unit (ICU) hospitalizations of very old patients with acute respiratory infection have risen. The decision-making process for ICU admission is multifaceted, and the prediction of long-term survival outcome is an important component. We hypothesized that data-driven algorithms could build long-term prediction by examining massive real-life data. Our objective was to assess ...
Recent advancements in diagnostic technologies have significantly transformed the landscape of respiratory medicine, aiming for early detection, improved specificity and personalized therapeutic strategies. Innovations in imaging such as multi-slice computed tomography (CT) scanners, high-resolution CT and magnetic resonance imaging (MRI) have revolutionized our ability to visualize and assess the...
This review paper comprehensively examines recent advancements in machine learning (ML) applications within biofluid mechanics, with a targeted focus ...
Central Apnea (CA) and Central Hypopnea (CH) are sleep disorders arising from the brain's inability to signal respiratory muscles, potentially leading...
Medical image segmentation plays a critical role in modern clinical diagnosis. However, existing methods face challenges such as insufficient feature ...
BACKGROUND: Distinguishing between productive (wet) and non-productive (dry) cough types is important for evaluating respiratory health, assisting in ...
The prediction of Intensive Care Unit (ICU) readmission has become a crucial area of research due to the increasing demand for ICU resources and the n...
In real-world scenarios, multi-view multi-label learning often encounters the challenge of incomplete training data due to limitations in data collect...
Time series anomaly detection is crucial for maintaining stable systems. Existing methods face two main challenges. First, it is difficult to directly...
A machine learning integrated SERS sensing platform is developed for a single-shot, receptor-free, rapid detection and classification of five respirat...
We introduce DABstep, a novel benchmark for evaluating AI agents on realistic multi-step data analysis tasks. DABstep comprises over 450 real-world ...
The purpose of this paper is to explore a multi-modal approach to enhancing live broadcast engagement by developing a short video recommendation sys...
Background: Conventional cardiovascular magnetic resonance (CMR) in paediatric and congenital heart disease uses 2D, breath-hold, balanced steady st...
Multi-task learning (MTL) has demonstrated significant advantages in the field of physiological signal measurement. This approach enhances the model's...
Accurate forecasting of ground-level ozone (O) is essential for assessing its public health and socioeconomic impacts. This study evaluates the perfor...
Large language models (LLMs) are increasingly used in clinical decision support, yet current evaluation methods often fail to distinguish genuine me...
Implicit Neural representations (INRs) have emerged as a promising approach for video compression, and have achieved comparable performance to the s...
Invasive mechanical ventilation (MV) is a life-sustaining therapy for critically ill patients in the intensive care unit (ICU). However, optimizing ...
Solving Inverse Kinematics (IK) problems is fundamental to robotics, but has primarily been successful with single serial manipulators. For multi-ar...
3D Gaussian Splatting (3DGS) has emerged as a preferred choice alongside Neural Radiance Fields (NeRF) in inverse rendering due to its superior rend...