Critical Care

TaughtNet: Learning Multi-Task Biomedical Named Entity Recognition From Single-Task Teachers.

In Biomedical Named Entity Recognition (BioNER), the use of current cutting-edge deep learning-based...

Application of an artificial intelligence ensemble for detection of important secondary findings on lung ventilation and perfusion SPECT-CT.

RATIONALE: Single-photon-emission-computerized-tomography/computed-tomography(SPECT/CT) is commonly ...

Implementation of digital home monitoring and management of respiratory disease.

PURPOSE OF REVIEW: Digital respiratory monitoring interventions (e.g. smart inhalers and digital spi...

Pharmacophenotype identification of intensive care unit medications using unsupervised cluster analysis of the ICURx common data model.

BACKGROUND: Identifying patterns within ICU medication regimens may help artificial intelligence alg...

MuRCL: Multi-Instance Reinforcement Contrastive Learning for Whole Slide Image Classification.

Multi-instance learning (MIL) is widely adop- ted for automatic whole slide image (WSI) analysis and...

Probabilistic double hierarchy linguistic Maclaurin symmetric mean-MultiCriteria Border Approximation area Comparison method for multi-criteria group decision making and its application in a selection of traditional Chinese medicine prescriptions.

Traditional Chinese medicine (TCM) has gradually played an indispensable role in people's health mai...

Neural gradient boosting in federated learning for hemodynamic instability prediction: towards a distributed and scalable deep learning-based solution.

Federated learning (FL) is a privacy preserving approach to learning that overcome issues related to...

Predictive Modeling Using Artificial Intelligence and Machine Learning Algorithms on Electronic Health Record Data: Advantages and Challenges.

The rapid adoption of electronic health record (EHR) systems in US hospitals from 2008 to 2014 produ...

Bringing the Promise of Artificial Intelligence to Critical Care: What the Experience With Sepsis Analytics Can Teach Us.

A multi-view co-training network for semi-supervised medical image-based prognostic prediction.

Prognostic prediction has long been a hotspot in disease analysis and management, and the developmen...

Hospital mortality prediction in traumatic injuries patients: comparing different SMOTE-based machine learning algorithms.

BACKGROUND: Trauma is one of the most critical public health issues worldwide, leading to death and ...

Developing DELPHI expert consensus rules for a digital twin model of acute stroke care in the neuro critical care unit.

INTRODUCTION: Digital twins, a form of artificial intelligence, are virtual representations of the p...

RIMD: A novel method for clinical prediction.

Electronic health records (EHR) are sparse, noisy, and private, with variable vital measurements and...

A Comparison of Signal Combinations for Deep Learning-Based Simultaneous Sleep Staging and Respiratory Event Detection.

OBJECTIVE: Obstructive sleep apnea (OSA) is diagnosed using the apnea-hypopnea index (AHI), which is...

The Past, Present, and Future Role of Artificial Intelligence in Ventilation/Perfusion Scintigraphy: A Systematic Review.

Ventilation-perfusion (V/Q) lung scans constitute one of the oldest nuclear medicine procedures, rem...

Deformable registration of lung 3DCT images using an unsupervised heterogeneous multi-resolution neural network.

Lung image registration is more challenging than other organs. This is because the breath of the hum...

[Video-assisted Double-lumen Tubes in Robot-assisted Oesophageal Surgery].

Robot-assisted esophagectomies are still considered high-risk procedures requiring complex surgical ...

Multi-event survival analysis through dynamic multi-modal learning for ICU mortality prediction.

BACKGROUND AND OBJECTIVE: Survival analysis is widely applied for assessing the expected duration of...

Gait-CNN-ViT: Multi-Model Gait Recognition with Convolutional Neural Networks and Vision Transformer.

Gait recognition, the task of identifying an individual based on their unique walking style, can be ...

The comforting companion: using AI to bring loved one's voices to newborns, infants, and unconscious patients in ICU.

A Multidatabase ExTRaction PipEline (METRE) for facile cross validation in critical care research.

Transforming raw EHR data into machine learning model-ready inputs requires considerable effort. One...