Sepsis

CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database.

The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation and interpretation of resistomes. As of version 3.2.4, CARD encompasses 6627 ontology terms, 5010 reference sequences, 1933 mutations, 3004 publication...

Detection of Ningnanmycin Using Fluorescence Spectroscopy Combined with BP Neural Network.

BACKGROUND: Ningnanmycin is a new antibiotic pesticide with good bactericidal and antiviral efficacy, which is widely used in the control of fruit and vegetable diseases, and the excessive pesticide residues pose a serious threat to the environment and human health.

Disposable Barrel Used for Easy and Fast Toe Space Examination.

Chronic candidiasis with bacterial infection is common infection in the toe web which is is not inspected and treated well in early stage, and it is n...

[Case of Robot-Assisted Low Anterior Resection with Total Cystectomy for Rectal Cancer Invading the Urinary Bladder/Prostate in Collaboration with Urologists].

We present a case of a 72-year-old man diagnosed with rectal cancer invading the urinary bladder/prostate. Preoperative chemoradiotherapy substantiall...

Comparison of Mortality Predictive Models of Sepsis Patients Based on Machine Learning.

Objective To compare the performance of five machine learning models and SAPS II score in predicting the 30-day mortality amongst patients with sepsis...

Identifying infected patients using semi-supervised and transfer learning.

OBJECTIVES: Early identification of infection improves outcomes, but developing models for early identification requires determining infection status ...

Lessons in machine learning model deployment learned from sepsis.

In three recent and related publications, researchers from Johns Hopkins University and Bayesian Health report results from implementing and prospecti...

A Riemannian Deep Learning Representation to Describe Gait Parkinsonian Locomotor Patterns.

Parkinson is the second most common neurodegenerative disease, mainly related to progressive locomotor alterations caused by dopamine deficiency. The ...

Analysis of classification tradeoff in deep learning for gastric cancer detection.

This study aimed to build convolutional neural network (CNN) models capable of classifying upper endoscopy images, to determine the stage of infection...

Machine Learning Used to Compare the Diagnostic Accuracy of Risk Factors, Clinical Signs and Biomarkers and to Develop a New Prediction Model for Neonatal Early-onset Sepsis.

BACKGROUND: Current strategies for risk stratification and prediction of neonatal early-onset sepsis (EOS) are inefficient and lack diagnostic perform...

Enhancing sepsis management through machine learning techniques: A review.

Sepsis is a major public health problem and a leading cause of death in the world, where delay in the beginning of treatment, along with clinical guid...

Automated extraction of genes associated with antibiotic resistance from the biomedical literature.

The detection of bacterial antibiotic resistance phenotypes is important when carrying out clinical decisions for patient treatment. Conventional phen...

Developing a Data Driven Approach for Early Detection of SIRS in Pediatric Intensive Care Using Automatically Labeled Training Data.

Critical care can benefit from analyzing data by machine learning approaches for supporting clinical routine and guiding clinical decision-making. Dev...

Classification by a stacking model using CNN features for COVID-19 infection diagnosis.

Affecting millions of people all over the world, the COVID-19 pandemic has caused the death of hundreds of thousands of people since its beginning. Ex...

Detection of COVID-19 Infection in CT and X-ray images using transfer learning approach.

BACKGROUND: The infection caused by the SARS-CoV-2 (COVID-19) pandemic is a threat to human lives. An early and accurate diagnosis is necessary for tr...

Treatment of Chronic Osteomyelitis of the Femur by Intramedullary Antibiotic Perfusion (iMAP): A Case Report.

INTRODUCTION: Chronic osteomyelitis is difficult to cure definitively, because local areas are often covered with sequestrum and scar tissues with a p...

De novo generation of dual-target ligands using adversarial training and reinforcement learning.

Artificial intelligence, such as deep generative methods, represents a promising solution to de novo design of molecules with the desired properties. ...

Machine learning for identifying resistance features of using whole-genome sequence single nucleotide polymorphisms.

, a gram-negative bacterium, is a common pathogen causing nosocomial infection. The drug-resistance rate of is increasing year by year, posing a sev...

A Machine Learning Understanding of Sepsis.

Sepsis is a serious cause of morbidity and mortality and yet its pathophysiology remains elusive. Recently, medical and technological advances have he...

Exploring Features Contributing to the Early Prediction of Sepsis Using Machine Learning.

The increasing availability of electronic health records and administrative data and the adoption of computer-based technologies in healthcare have si...