Sepsis

Pre-Trained Deep Convolutional Neural Network for Clostridioides Difficile Bacteria Cytotoxicity Classification Based on Fluorescence Images.

infection (CDI) is an enteric bacterial disease that is increasing in incidence worldwide. Symptoms of CDI range from mild diarrhea to severe life-threatening inflammation of the colon. While antibiotics are standard-of-care treatments for CDI, they are also the biggest risk factor for development of CDI and recurrence. Therefore, novel therapies that successfully treat CDI and protect against re...

Machine Learning Approaches Reveal That the Number of Tests Do Not Matter to the Prediction of Global Confirmed COVID-19 Cases.

Coronavirus disease 2019 (COVID-19) has developed into a global pandemic, affecting every nation and territory in the world. Machine learning-based approaches are useful when trying to understand the complexity behind the spread of the disease and how to contain its spread effectively. The unsupervised learning method could be useful to evaluate the shortcomings of health facilities in areas of in...

A neural network for prediction of risk of nosocomial infection at intensive care units: a didactic preliminary model.

OBJECTIVE: To propose a preliminary artificial intelligence model, based on artificial neural networks, for predicting the risk of nosocomial infectio...

Renal function in children infected with : a case-control study of an endemic Ghanaian community.

Schistosomiasis has been associated with kidney diseases leading to serious health problems especially in advanced cases. Most studies have used renal...

Development and utility assessment of a machine learning bloodstream infection classifier in pediatric patients receiving cancer treatments.

BACKGROUND: Objectives were to build a machine learning algorithm to identify bloodstream infection (BSI) among pediatric patients with cancer and hem...

Comparison of Different Dosages and Volumes of Triamcinolone in the Treatment of Stenosing Tenosynovitis: A Prospective, Blinded, Randomized Trial.

BACKGROUND: Stenosing tenosynovitis is a condition due to a size mismatch between the flexor tendons and the first annular pulley. Corticosteroid inje...

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 infections, and it is a leading cause of morbidity and mo...

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 successful treatment. Genome wide expression profil...

Safety and efficacy of robot-assisted versus open pancreaticoduodenectomy: a meta-analysis of multiple worldwide centers.

The objective of the study is to compare the safety and efficacy of robot-assisted pancreaticoduodenectomy (PD) with open PD. The PubMed, EMBASE and C...

Artificial Intelligence in the Intensive Care Unit.

The diffusion of electronic health records collecting large amount of clinical, monitoring, and laboratory data produced by intensive care units (ICUs...

A gradient boosting machine learning approach in modeling the impact of temperature and humidity on the transmission rate of COVID-19 in India.

Meteorological parameters were crucial and effective factors in past infectious diseases, like influenza and severe acute respiratory syndrome (SARS),...

Machine learning prediction for mortality of patients diagnosed with COVID-19: a nationwide Korean cohort study.

The rapid spread of COVID-19 has resulted in the shortage of medical resources, which necessitates accurate prognosis prediction to triage patients ef...

A deep learning approach for sepsis monitoring via severity score estimation.

BACKGROUND AND OBJECTIVE: Sepsis occurs in response to an infection in the body and can progress to a fatal stage. Detection and monitoring of sepsis ...

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 early stage β-coronavirus severe acute respiratory ...

Validation of a machine learning algorithm for early severe sepsis prediction: a retrospective study predicting severe sepsis up to 48 h in advance using a diverse dataset from 461 US hospitals.

BACKGROUND: Severe sepsis and septic shock are among the leading causes of death in the United States and sepsis remains one of the most expensive con...

Temporal variation and sharing of antibiotic resistance genes between water and wild fish gut in a peri-urban river.

Antibiotic resistance genes (ARGs) as emergence contaminations have spread widely in the water environment. Wild fish may be recipients and communicat...

Deep Learning Analysis of Vibrational Spectra of Bacterial Lysate for Rapid Antimicrobial Susceptibility Testing.

Rapid antimicrobial susceptibility testing (AST) is an integral tool to mitigate the unnecessary use of powerful and broad-spectrum antibiotics that l...

Infusion of short chain fatty acids in the ileum improves the carcass traits, meat quality and lipid metabolism of growing pigs.

Short chain fatty acids (SCFA) are the main products of indigestible carbohydrates undergoing bacterial fermentation in the hindgut, which are related...

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

As the prevalence of obesity climbs, dosing of antimicrobials, particularly cephalosporins, is becoming a greater challenge for clinicians. Data are ...

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 Computed Tomography (CT) scans, and the classificat...