Critical Care

Latest AI and machine learning research in critical care for healthcare professionals.

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Subcategories: Sepsis
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DMMAN: A two-stage audio-visual fusion framework for sound separation and event localization.

Videos are used widely as the media platforms for human beings to touch the physical change of the w...

Simulated four-dimensional CT for markerless tumor tracking using a deep learning network with multi-task learning.

INTRODUCTION: Our markerless tumor tracking algorithm requires 4DCT data to train models. 4DCT canno...

Prognostic Assessment of COVID-19 in the Intensive Care Unit by Machine Learning Methods: Model Development and Validation.

BACKGROUND: Patients with COVID-19 in the intensive care unit (ICU) have a high mortality rate, and ...

SSP: Early prediction of sepsis using fully connected LSTM-CNN model.

BACKGROUND: Sepsis is a life-threatening condition that occurs due to the body's reaction to infecti...

Deep learning-based clustering robustly identified two classes of sepsis with both prognostic and predictive values.

BACKGROUND: Sepsis is a heterogenous syndrome and individualized management strategy is the key to s...

Artificial Intelligence in the Intensive Care Unit.

The diffusion of electronic health records collecting large amount of clinical, monitoring, and labo...

Automated stroke lesion segmentation in non-contrast CT scans using dense multi-path contextual generative adversarial network.

Stroke lesion volume is a key radiologic measurement in assessing prognosis of acute ischemic stroke...

A Multi-View Deep Neural Network Model for Chemical-Disease Relation Extraction From Imbalanced Datasets.

Understanding the chemical-disease relations (CDR) is a crucial task in various biomedical domains. ...

A deep learning framework for pancreas segmentation with multi-atlas registration and 3D level-set.

In this paper, we propose and validate a deep learning framework that incorporates both multi-atlas ...

Electrochemical SARS-CoV-2 Sensing at Point-of-Care and Artificial Intelligence for Intelligent COVID-19 Management.

To manage the COVID-19 pandemic, development of rapid, selective, sensitive diagnostic systems for e...

Explainable Machine Learning for Early Assessment of COVID-19 Risk Prediction in Emergency Departments.

Between January and October of 2020, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2...

Effect of Obesity on Clinical Outcomes of Patients Treated With Cefepime.

As the prevalence of obesity climbs, dosing of antimicrobials, particularly cephalosporins, is beco...

Predicting Deep Learning Based Multi-Omics Parallel Integration Survival Subtypes in Lung Cancer Using Reverse Phase Protein Array Data.

Mortality attributed to lung cancer accounts for a large fraction of cancer deaths worldwide. With i...

A multi-task pipeline with specialized streams for classification and segmentation of infection manifestations in COVID-19 scans.

We are concerned with the challenge of coronavirus disease (COVID-19) detection in chest X-ray and C...

Path Planning of Mobile Robots Based on a Multi-Population Migration Genetic Algorithm.

In the field of robot path planning, aiming at the problems of the standard genetic algorithm, such ...

Diagnosis of common pulmonary diseases in children by X-ray images and deep learning.

Acute lower respiratory infection is the leading cause of child death in developing countries. Curre...

A Correlation-Driven Mapping For Deep Learning application in detecting artifacts within the EEG.

OBJECTIVE: When developing approaches for automatic preprocessing of electroencephalogram (EEG) sign...

Statistical and Machine-Learning Analyses in Nutritional Genomics Studies.

Nutritional compounds may have an influence on different OMICs levels, including genomics, epigenomi...

Graphical Presentations of Clinical Data in a Learning Electronic Medical Record.

BACKGROUND: Complex electronic medical records (EMRs) presenting large amounts of data create risks ...

The parable of arable land: Characterizing large scale land acquisitions through network analysis.

Land is a scarce resource and its depletion is related to a combination of demographic and economic ...

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