Sepsis

Predicting Sepsis Mortality in a Population-Based National Database: Machine Learning Approach.

BACKGROUND: Although machine learning (ML) algorithms have been applied to point-of-care sepsis prog...

Antilogic, a new supervised machine learning software for the automatic interpretation of antibiotic susceptibility testing in clinical microbiology: proof-of-concept on three frequently isolated bacterial species.

OBJECTIVE: Antibiotic susceptibility testing (AST) is necessary in order to adjust empirical antibio...

Fusion of fully integrated analog machine learning classifier with electronic medical records for real-time prediction of sepsis onset.

The objective of this work is to develop a fusion artificial intelligence (AI) model that combines p...

Machine learning predicts blood lactate levels in children after cardiac surgery in paediatric ICU.

BACKGROUND: Although serum lactate levels are widely accepted markers of haemodynamic instability, a...

Sepsis labels defined by claims-based methods are ill-suited for training machine learning algorithms.

A Machine Learning Model for Early Prediction and Detection of Sepsis in Intensive Care Unit Patients.

In today's scenario, sepsis is impacting millions of patients in the intensive care unit due to the ...

Exploration in neo-Hebbian reinforcement learning: Computational approaches to the exploration-exploitation balance with bio-inspired neural networks.

Recent theoretical and experimental works have connected Hebbian plasticity with the reinforcement l...

Artificial Intelligence in Infection Management in the ICU.

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency M...

Human-level COVID-19 diagnosis from low-dose CT scans using a two-stage time-distributed capsule network.

Reverse transcription-polymerase chain reaction is currently the gold standard in COVID-19 diagnosis...

Study on Automatic Multi-Classification of Spine Based on Deep Learning and Postoperative Infection Screening.

The preoperative qualitative and hierarchical diagnosis of intervertebral foramen stenosis is very i...

EDNC: Ensemble Deep Neural Network for COVID-19 Recognition.

The automatic recognition of COVID-19 diseases is critical in the present pandemic since it relieves...

Characteristics of Computed Tomography Images for Patients with Acute Liver Injury Caused by Sepsis under Deep Learning Algorithm.

This study was aimed at exploring the application of image segmentation based on full convolutional ...

Dietary supplementation of propolis enhanced the innate immune response against Edwardsiella piscicida challenge in turbot (Scophthalmus maximus).

Propolis is non-hazardous resinous substance mixture containing bioactive ingredients such as polyph...

Identification of Novel Noninvasive Diagnostics Biomarkers in the Parkinson's Diseases and Improving the Disease Classification Using Support Vector Machine.

BACKGROUND: Parkinson's disease (PD) is a neurological disorder that is marked by the deficit of neu...

Combining graph neural networks and spatio-temporal disease models to improve the prediction of weekly COVID-19 cases in Germany.

During 2020, the infection rate of COVID-19 has been investigated by many scholars from different re...

Advanced medical monitoring for the battlefield: A review on clinical applicability of compensatory reserve measurements for early and accurate hemorrhage detection.

Hemorrhagic shock remains the leading cause of mortality in civilian trauma and battlefield settings...

Profiling of 35 Cases of Hb S/Hb E (: c.20A>T/: c.79G>a), Disease and Association with α-Thalassemia and β-Globin Gene Cluster Haplotypes from Odisha, India.

Hb S/Hb E (: c.20A>T/: c.79G>A) is an uncommon variant of sickle cell disease resulting from coinher...

Identification of antimicrobial peptides from the human gut microbiome using deep learning.

The human gut microbiome encodes a large variety of antimicrobial peptides (AMPs), but the short len...

INASNET: Automatic identification of coronavirus disease (COVID-19) based on chest X-ray using deep neural network.

Testing is one of the important methodologies used by various countries in order to fight against CO...

Anti-Fatigue and Exercise Performance Improvement Effect of Extract in Mice.

(GT) is a native perennial plant growing across the coastline areas in Taiwan. The current study ai...

Anticipating antibiotic resistance.

Machine learning can use clinical history to lower the risk of infection recurrence.