Intensivists

AMSUnet: A neural network using atrous multi-scale convolution for medical image segmentation.

In recent years, Unet and its variants have gained astounding success in the realm of medical image ...

Fast and Calibrationless Low-Rank Parallel Imaging Reconstruction Through Unrolled Deep Learning Estimation of Multi-Channel Spatial Support Maps.

Low-rank technique has emerged as a powerful calibrationless alternative for parallel magnetic reson...

BrainS: Customized multi-core embedded multiple scale neuromorphic system.

Research on modeling and mechanisms of the brain remains the most urgent and challenging task. The c...

Strategy to implement a convolutional neural network based ideal model observer via transfer learning for multi-slice simulated breast CT images.

In this work, we propose a convolutional neural network (CNN)-based multi-slice ideal model observer...

A Convex Optimization Approach to Multi-Robot Task Allocation and Path Planning.

In real-world applications, multiple robots need to be dynamically deployed to their appropriate loc...

NSICA: Multi-objective imperialist competitive algorithm for feature selection in arrhythmia diagnosis.

This study proposes a multi-objective, non-dominated, imperialist competitive algorithm (NSICA) to s...

The Evolution and Future of Intensive Care Management in the Era of Telecritical Care and Artificial Intelligence.

Critical care practice has been embodied in the healthcare system since the institutionalization of ...

Identifying acute kidney injury subphenotypes using an outcome-driven deep-learning approach.

OBJECTIVE: Acute kidney injury (AKI), a common condition on the intensive-care unit (ICU), is charac...

Artificial Intelligence in Intensive Care Medicine: Toward a ChatGPT/GPT-4 Way?

Although intensive care medicine (ICM) is a relatively young discipline, it has rapidly developed in...

Human Collective Intelligence Inspired Multi-View Representation Learning - Enabling View Communication by Simulating Human Communication Mechanism.

In real-world applications, we often encounter multi-view learning tasks where we need to learn from...

EgoCom: A Multi-Person Multi-Modal Egocentric Communications Dataset.

Multi-modal datasets in artificial intelligence (AI) often capture a third-person perspective, but o...

A dosing strategy model of deep deterministic policy gradient algorithm for sepsis patients.

BACKGROUND: A growing body of research suggests that the use of computerized decision support system...

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...

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...

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...