Intensivists

Adaptive Multi-Modal Fusion Framework for Activity Monitoring of People With Mobility Disability.

The development of activity recognition based on multi-modal data makes it possible to reduce human intervention in the process of monitoring. This paper proposes an efficient and cost-effective multi-modal sensing framework for activity monitoring, it can automatically identify human activities based on multi-modal data, and provide help to patients with moderate disabilities. The multi-modal sen...

Dynamic Sepsis Prediction for Intensive Care Unit Patients Using XGBoost-Based Model With Novel Time-Dependent Features.

Sepsis is a systemic inflammatory response caused by pathogens such as bacteria. Because its pathogenesis is not clear, the clinical manifestations of patients vary greatly, and the alarming incidence and mortality pose a great threat to patients and medical systems, especially in the ICU (Intensive Care Unit). The traditional judgment criteria have the problem of low specificity. Artificial intel...

A graph-based approach to multi-source heterogeneous information fusion in stock market.

The stock market is an important part of the capital market, and the research on the price fluctuation of the stock market has always been a hot topic...

Explainable Artificial Intelligence Helps in Understanding the Effect of Fibronectin on Survival of Sepsis.

Fibronectin (FN) plays an essential role in the host's response to infection. In previous studies, a significant decrease in the FN level was observed...

Prediction algorithm for ICU mortality and length of stay using machine learning.

Machine learning can predict outcomes and determine variables contributing to precise prediction, and can thus classify patients with different risk f...

A Two-Stream Graph Convolutional Network Based on Brain Connectivity for Anesthetized States Analysis.

Investigating neural mechanisms of anesthesia process and developing efficient anesthetized state detection methods are especially on high demand for ...

Factors driving provider adoption of the TREWS machine learning-based early warning system and its effects on sepsis treatment timing.

Machine learning-based clinical decision support tools for sepsis create opportunities to identify at-risk patients and initiate treatments at early t...

Protocol to predict mechanical properties of multi-element ceramics using machine learning.

Identifying and designing high-performance multi-element ceramics based on trial-and-error approaches are ineffective and expensive. Here, we present ...

Neural Network Based IRSs-UEs Association and IRSs Optimal Placement in Multi IRSs Aided Wireless System.

Implementing intelligent reflecting surfaces (IRSs), in high frequency based beyond 5G networks, has become a necessity to overcome the harsh blockage...

Artificial intelligence (AI) versus expert: A comparison of left ventricular outflow tract velocity time integral (LVOT-VTI) assessment between ICU doctors and an AI tool.

PURPOSE: The application of point of care ultrasound (PoCUS) in medical education is a relatively new course. There are still great differences in the...

Interval-valued intuitionistic fuzzy multi-attribute group decision-making method considering risk preference of decision-makers and its application.

An improved interval-valued intuitionistic fuzzy multi-attribute group decision-making method considering the risk preference of decision-makers is pr...

European Society of Paediatric Radiology Artificial Intelligence taskforce: a new taskforce for the digital age.

A new task force dedicated to artificial intelligence (AI) with respect to paediatric radiology was created in 2021 at the International Paediatric Ra...

Large-scale investigation of deep learning approaches for ventilated lung segmentation using multi-nuclear hyperpolarized gas MRI.

Respiratory diseases are leading causes of mortality and morbidity worldwide. Pulmonary imaging is an essential component of the diagnosis, treatment ...

Highlights of the Virtual Society for Cardiovascular Magnetic Resonance 2022 Scientific Conference: CMR: improving cardiovascular care around the world.

The 25th Society for Cardiovascular Magnetic Resonance (SCMR) Annual Scientific Sessions saw 1524 registered participants from more than 50 countries ...

Tell me something interesting: Clinical utility of machine learning prediction models in the ICU.

In recent years, extensive resources are dedicated to the development of machine learning (ML) based clinical prediction models for intensive care uni...

Deep learning-based lesion subtyping and prediction of clinical outcomes in COVID-19 pneumonia using chest CT.

The main objective of this work is to develop and evaluate an artificial intelligence system based on deep learning capable of automatically identifyi...

Nanostructured block copolymer muscles.

High-performance actuating materials are necessary for advances in robotics, prosthetics and smart clothing. Here we report a class of fibre actuators...

Risk assessment of ICU patients through deep learning technique: A big data approach.

BACKGROUND: Intensive Care Unit (ICU) patients are exposed to various medications, especially during infusion, and the amount of infusion drugs and th...

Development of a deep learning model that predicts Bi-level positive airway pressure failure.

Delaying intubation for patients failing Bi-Level Positive Airway Pressure (BIPAP) may be associated with harm. The objective of this study was to dev...

Leveraging clinical data across healthcare institutions for continual learning of predictive risk models.

The inherent flexibility of machine learning-based clinical predictive models to learn from episodes of patient care at a new institution (site-specif...