Critical Care

Sepsis

Latest AI and machine learning research in sepsis for healthcare professionals.

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Critical-Care Subcategories: Sepsis
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Machine learning application for the prediction of SARS-CoV-2 infection using blood tests and chest radiograph.

Triaging and prioritising patients for RT-PCR test had been essential in the management of COVID-19 ...

Dual-Organ Transcriptomic Analysis of Rainbow Trout Infected With Through Co-Expression and Machine Learning.

is a major pathogen that causes a high mortality rate in trout farms. However, systemic responses t...

Timesias: A machine learning pipeline for predicting outcomes from time-series clinical records.

The prediction of outcomes is a critical part of the clinical surveillance for hospitalized patients...

On the Role of Arkypallidal and Prototypical Neurons for Phase Transitions in the External Pallidum.

The external pallidum (globus pallidus pars externa [GPe]) plays a central role for basal ganglia fu...

Face mask detection using deep learning: An approach to reduce risk of Coronavirus spread.

Effective strategies to restrain COVID-19 pandemic need high attention to mitigate negatively impact...

Automated Data Quality Control in FDOPA brain PET Imaging using Deep Learning.

INTRODUCTION: With biomedical imaging research increasingly using large datasets, it becomes critica...

A Pragmatic Machine Learning Model To Predict Carbapenem Resistance.

Infection caused by carbapenem-resistant (CR) organisms is a rising problem in the United States. Wh...

One-step-immunoassay of procalcitonin enables rapid and accurate diagnosis of bacterial infection.

Procalcitonin (PCT) ( a precursor of calcitonin) attracts much attention as a reliable biomarker of ...

Profiling single-cell level phagocytic activity distribution with blood lactate levels.

The ability to kill infecting microbes is an essential facet of our immune response to an infection....

Exploring prevalence of wound infections and related patient characteristics in homecare using natural language processing.

We aimed to create and validate a natural language processing algorithm to extract wound infection-r...

Deep Learning on Chest X-ray Images to Detect and Evaluate Pneumonia Cases at the Era of COVID-19.

Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu....

An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19.

Pneumonia is an infamous life-threatening lung bacterial or viral infection. The latest viral infect...

Meta-control: From psychology to computational neuroscience.

Research in the past decades shed light on the different mechanisms that underlie our capacity for c...

Multilevel Deep-Aggregated Boosted Network to Recognize COVID-19 Infection from Large-Scale Heterogeneous Radiographic Data.

In the present epidemic of the coronavirus disease 2019 (COVID-19), radiological imaging modalities,...

Spine dynamics in the brain, mental disorders and artificial neural networks.

In the brain, most synapses are formed on minute protrusions known as dendritic spines. Unlike their...

Kinematics approach with neural networks for early detection of sepsis (KANNEDS).

BACKGROUND: Sepsis is a severe illness that affects millions of people worldwide, and its early dete...

Segmenting lung lesions of COVID-19 from CT images via pyramid pooling improved Unet.

Segmenting lesion regions of Coronavirus Disease 2019 (COVID-19) from computed tomography (CT) image...

Comparison of machine-learning methodologies for accurate diagnosis of sepsis using microarray gene expression data.

We investigate the feasibility of molecular-level sample classification of sepsis using microarray g...

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