Sepsis

Artificial Intelligence for the Prediction of Helicobacter Pylori Infection in Endoscopic Images: Systematic Review and Meta-Analysis Of Diagnostic Test Accuracy.

BACKGROUND: Helicobacter pylori plays a central role in the development of gastric cancer, and prediction of H pylori infection by visual inspection of the gastric mucosa is an important function of endoscopy. However, there are currently no established methods of optical diagnosis of H pylori infection using endoscopic images. Definitive diagnosis requires endoscopic biopsy. Artificial intelligen...

Toward a hemorrhagic trauma severity score: fusing five physiological biomarkers.

BACKGROUND: To introduce the Hemorrhage Intensive Severity and Survivability (HISS) score, based on the fusion of multi-biomarker data; glucose, lactate, pH, potassium, and oxygen tension, to serve as a patient-specific attribute in hemorrhagic trauma.

Supervised classification techniques for prediction of mortality in adult patients with sepsis.

BACKGROUND: Sepsis mortality is still unacceptably high and an appropriate prognostic tool may increase the accuracy for clinical decisions.

A Deep-Learning View of Chemical Space Designed to Facilitate Drug Discovery.

Drug discovery projects entail cycles of design, synthesis, and testing that yield a series of chemically related small molecules whose properties, su...

Pilot Study of Robot-Assisted Teleultrasound Based on 5G Network: A New Feasible Strategy for Early Imaging Assessment During COVID-19 Pandemic.

Early diagnosis is critical for the prevention and control of the coronavirus disease 2019 (COVID-19). We attempted to apply a protocol using teleultr...

Machine learning based refined differential gene expression analysis of pediatric sepsis.

BACKGROUND: Differential expression (DE) analysis of transcriptomic data enables genome-wide analysis of gene expression changes associated with biolo...

Predicting Coronavirus Disease 2019 Infection Risk and Related Risk Drivers in Nursing Homes: A Machine Learning Approach.

OBJECTIVE: Inform coronavirus disease 2019 (COVID-19) infection prevention measures by identifying and assessing risk and possible vectors of infectio...

A Basal Ganglia Computational Model to Explain the Paradoxical Sensorial Improvement in the Presence of Huntington's Disease.

The basal ganglia (BG) represent a critical center of the nervous system for sensorial discrimination. Although it is known that Huntington's disease ...

Incessant Pericarditis With Recurrent Cardiac Tamponade as the Manifestation of Autoimmune Polyglandular Syndrome Type II.

A 23-year-old man was admitted for acute pericarditis that evolved to cardiac tamponade and shock with need of emergent pericardiocentesis and inotrop...

Improved Antibiotic Detection in Raw Milk Using Machine Learning Tools over the Absorption Spectra of a Problem-Specific Nanobiosensor.

In this article we present the development of a biosensor system that integrates nanotechnology, optomechanics and a spectral detection algorithm for ...

Morphological Characterization of Functional Brain Imaging by Isosurface Analysis in Parkinson's Disease.

Finding new biomarkers to model Parkinson's Disease (PD) is a challenge not only to help discerning between Healthy Control (HC) subjects and patients...

A Novel Approach for Continuous Health Status Monitoring and Automatic Detection of Infection Incidences in People With Type 1 Diabetes Using Machine Learning Algorithms (Part 2): A Personalized Digital Infectious Disease Detection Mechanism.

BACKGROUND: Semisupervised and unsupervised anomaly detection methods have been widely used in various applications to detect anomalous objects from a...

A Single-Center Evaluation of Extended Infusion Piperacillin/Tazobactam for Empiric Treatment in the Intensive Care Unit.

Piperacillin/tazobactam (PTZ) extended infusion (EI) is often used empirically in the intensive care unit (ICU). Gram-negative (GN) organisms with PT...

Detection of Bacteremia in Surgical In-Patients Using Recurrent Neural Network Based on Time Series Records: Development and Validation Study.

BACKGROUND: Detecting bacteremia among surgical in-patients is more obscure than other patients due to the inflammatory condition caused by the surger...

Development and validation of prognosis model of mortality risk in patients with COVID-19.

This study aimed to identify clinical features for prognosing mortality risk using machine-learning methods in patients with coronavirus disease 2019 ...

Validation of the usefulness of artificial neural networks for risk prediction of adverse drug reactions used for individual patients in clinical practice.

Artificial neural networks are the main tools for data mining and were inspired by the human brain and nervous system. Studies have demonstrated their...

Deep transfer learning artificial intelligence accurately stages COVID-19 lung disease severity on portable chest radiographs.

This study employed deep-learning convolutional neural networks to stage lung disease severity of Coronavirus Disease 2019 (COVID-19) infection on por...

Machine Learning Algorithms Identify Pathogen-Specific Biomarkers of Clinical and Metabolomic Characteristics in Septic Patients with Bacterial Infections.

Sepsis is a high-mortality disease that is infected by bacteria, but pathogens in individual patients are difficult to diagnosis. Metabolomic changes ...

Novel application of an automated-machine learning development tool for predicting burn sepsis: proof of concept.

Sepsis is the primary cause of burn-related mortality and morbidity. Traditional indicators of sepsis exhibit poor performance when used in this uniqu...

Lightweight Learning-Based Automatic Segmentation of Subretinal Blebs on Microscope-Integrated Optical Coherence Tomography Images.

PURPOSE: Subretinal injections of therapeutics are commonly used to treat ocular diseases. Accurate dosing of therapeutics at target locations is cruc...