Critical Care

Sepsis

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

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Showing 841-861 of 9,021 articles
Antibiotic discovery in the artificial intelligence era.

As the global burden of antibiotic resistance continues to grow, creative approaches to antibiotic d...

Unsupervised landmark detection and classification of lung infection using transporter neural networks.

Supervised deep learning techniques have been very popular in medical imaging for various tasks of c...

Identification of two robust subclasses of sepsis with both prognostic and therapeutic values based on machine learning analysis.

BACKGROUND: Sepsis is a heterogeneous syndrome with high morbidity and mortality. Optimal and effect...

An optimistic firefly algorithm-based deep learning approach for sentiment analysis of COVID-19 tweets.

The unprecedented rise in the number of COVID-19 cases has drawn global attention, as it has caused ...

Machine Learning with Neural Networks to Enhance Selectivity of Nonenzymatic Electrochemical Biosensors in Multianalyte Mixtures.

Nonenzymatic biosensors hold great potential in the field of analysis and detection due to long-term...

Diagnostic performance of machine learning models using cell population data for the detection of sepsis: a comparative study.

OBJECTIVES: To compare the artificial intelligence algorithms as powerful machine learning methods f...

The Health Gym: synthetic health-related datasets for the development of reinforcement learning algorithms.

In recent years, the machine learning research community has benefited tremendously from the availab...

Generative adversarial network based data augmentation for CNN based detection of Covid-19.

Covid-19 has been a global concern since 2019, crippling the world economy and health. Biological di...

Explainable Deep-Learning-Assisted Sweat Assessment via a Programmable Colorimetric Chip.

Multianalytes and individual differences of biofluids (such as blood, urine, or sweat) pose enormous...

Progress in Control-Actuation Robotic System for Gastrointestinal NOTES Development.

PURPOSE: Natural orifice transluminal endoscopic surgery (NOTES) is a minimally invasive surgical pr...

In-sensor neural network for high energy efficiency analog-to-information conversion.

This work presents an on-chip analog-to-information conversion technique that utilizes analog hyper-...

Predicting risk of sepsis, comparison between machine learning methods: a case study of a Virginia hospital.

Sepsis is an inflammation caused by the body's systemic response to an infection. The infection coul...

Automated system for classification of COVID-19 infection from lung CT images based on machine learning and deep learning techniques.

The objectives of our proposed study were as follows: First objective is to segment the CT images us...

Analysis of Characteristic Factors of Nursing Safety Incidents in ENT Surgery by Deep Learning-Based Medical Data Association Rules Method.

It is of great significance to explore the characteristic factors of postoperative nursing safety ev...

Active deep learning from a noisy teacher for semi-supervised 3D image segmentation: Application to COVID-19 pneumonia infection in CT.

Supervised deep learning has become a standard approach to solving medical image segmentation tasks....

Dynamic feature learning for COVID-19 segmentation and classification.

Since December 2019, coronavirus SARS-CoV-2 (COVID-19) has rapidly developed into a global epidemic,...

An interpretable machine learning model for selectivity of small-molecules against homologous protein family.

In the early stages of drug discovery, various experimental and computational methods are used to m...

Deep Learning-Based Medical Data Association Rules to Explore the Connectivity and Regulation Mechanism of miRNA-mRNA Network in Myocarditis.

Acute, chronic myocarditis as myocardial localized or diffuse inflammation lesions is usually involv...

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