Sepsis

High Accuracy of Convolutional Neural Network for Evaluation of Helicobacter pylori Infection Based on Endoscopic Images: Preliminary Experience.

OBJECTIVES: Application of artificial intelligence in gastrointestinal endoscopy is increasing. The ...

A Machine Learning-Based Triage Tool for Children With Acute Infection in a Low Resource Setting.

OBJECTIVES: To deploy machine learning tools (random forests) to develop a model that reliably predi...

A guide to machine learning for bacterial host attribution using genome sequence data.

With the ever-expanding number of available sequences from bacterial genomes, and the expectation th...

Assessing clinical heterogeneity in sepsis through treatment patterns and machine learning.

OBJECTIVE: To use unsupervised topic modeling to evaluate heterogeneity in sepsis treatment patterns...

Artificial Neural Network-Based Prediction of Outcome in Parkinson's Disease Patients Using DaTscan SPECT Imaging Features.

PURPOSE: Quantitative analysis of dopamine transporter (DAT) single-photon emission computed tomogra...

In vitro cytotoxic, antioxidant, antibacterial and antifungal activity of Saussurea heteromalla indigenous to Pakistan.

Medicinal plants are proven to reveal vast promising potential providing novel drug candidates to co...

A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice.

OBJECTIVES: Develop and implement a machine learning algorithm to predict severe sepsis and septic s...

Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock.

OBJECTIVE: To assess clinician perceptions of a machine learning-based early warning system to predi...

Risk stratification of cervical lesions using capture sequencing and machine learning method based on HPV and human integrated genomic profiles.

From initial human papillomavirus (HPV) infection and precursor stages, the development of cervical ...

A Double-Blind, Randomized Control Trial of Rapidly Infused High Strong Ion Difference (SID) Fluid Versus Hartmann's Solution on Acid-Base Status in Sepsis Patients in the Emergency Department.

BACKGROUND: Balanced fluids are preferred in initial resuscitation of septic patients based on sever...

A new and efficient numerical method for the fractional modeling and optimal control of diabetes and tuberculosis co-existence.

The main objective of this research is to investigate a new fractional mathematical model involving ...

Prospect of using deep learning for predicting differentiation of myeloid progenitor cells after sepsis.

Machine learning applications for the prediction of surgical site infection in neurological operations.

OBJECTIVE: Surgical site infection (SSI) following a neurosurgical operation is a complication that ...

Application of Machine Learning to Prediction of Surgical Site Infection.

Surgical site infections are an important health concern, particularly in low-resource areas, where ...

Machine-learning-assisted selection of antibiotic prescription.

Artificial intelligence can improve decision-making in infection management.

New Phenotypes for Sepsis: The Promise and Problem of Applying Machine Learning and Artificial Intelligence in Clinical Research.

Supervised machine learning for the prediction of infection on admission to hospital: a prospective observational cohort study.

BACKGROUND: Infection diagnosis can be challenging, relying on clinical judgement and non-specific m...

High-throughput screening and Bayesian machine learning for copper-dependent inhibitors of Staphylococcus aureus.

One potential source of new antibacterials is through probing existing chemical libraries for copper...

Heart rate variability based machine learning models for risk prediction of suspected sepsis patients in the emergency department.

Early identification of high-risk septic patients in the emergency department (ED) may guide appropr...

Lyapunov functional for virus infection model with diffusion and state-dependent delays.

In this paper, a virus dynamics model with diffusion, state-dependent delays and a general nonlinear...