Sepsis

Abnormal lung quantification in chest CT images of COVID-19 patients with deep learning and its application to severity prediction.

OBJECTIVE: Computed tomography (CT) provides rich diagnosis and severity information of COVID-19 in clinical practice. However, there is no computerized tool to automatically delineate COVID-19 infection regions in chest CT scans for quantitative assessment in advanced applications such as severity prediction. The aim of this study was to develop a deep learning (DL)-based method for automatic seg...

Improved motor outcome prediction in Parkinson's disease applying deep learning to DaTscan SPECT images.

PURPOSE: Dopamine transporter (DAT) SPECT imaging is routinely used in the diagnosis of Parkinson's disease (PD). Our previous efforts demonstrated the use of DAT SPECT images in a data-driven manner by improving prediction of PD clinical assessment outcome using radiomic features. In this work, we develop a convolutional neural network (CNN) based technique to predict clinical motor function eval...

Individualized prediction of COVID-19 adverse outcomes with MLHO.

The COVID-19 pandemic has devastated the world with health and economic wreckage. Precise estimates of adverse outcomes from COVID-19 could have led t...

Clinical Features of Emergency Department Patients from Early COVID-19 Pandemic that Predict SARS-CoV-2 Infection: Machine-learning Approach.

INTRODUCTION: Within a few months coronavirus disease 2019 (COVID-19) evolved into a pandemic causing millions of cases worldwide, but it remains chal...

A novel nano-lanthanum complex: synthesis, characterization and application as a macrofuran chemosensor in pharmaceutical, biological and environmental samples.

Macrofuran is widely used as an antibiotic for the treatment of urinary tract infections. Nevertheless, it is prohibited due to toxicity and environme...

Prediction of antibiotic-resistance genes occurrence at a recreational beach with deep learning models.

Antibiotic resistance genes (ARGs) have been reported to threaten the public health of beachgoers worldwide. Although ARG monitoring and beach guideli...

COVID-19 Recognition Using Ensemble-CNNs in Two New Chest X-ray Databases.

The recognition of COVID-19 infection from X-ray images is an emerging field in the learning and computer vision community. Despite the great efforts ...

Prediction of Sepsis in COVID-19 Using Laboratory Indicators.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has become a global public health concern. Many inpatients with COVID-19 have shown cl...

Analysis of protein determinants of host-specific infection properties of polyomaviruses using machine learning.

BACKGROUND: The large tumor antigen (LT-Ag) and major capsid protein VP1 are known to play important roles in determining the host-specific infection ...

Propagation source identification of infectious diseases with graph convolutional networks.

Source identification in networks has drawn considerable interest to understand and control the infectious disease propagation processes. It is usuall...

JCS: An Explainable COVID-19 Diagnosis System by Joint Classification and Segmentation.

Recently, the coronavirus disease 2019 (COVID-19) has caused a pandemic disease in over 200 countries, influencing billions of humans. To control the ...

Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission.

A complicated clinical course for critically ill patients admitted to the intensive care unit (ICU) usually includes multiorgan dysfunction and subseq...

Predicting presumed serious infection among hospitalized children on central venous lines with machine learning.

BACKGROUND: Presumed serious infection (PSI) is defined as a blood culture drawn and new antibiotic course of at least 4 days among pediatric patients...

AI-based mobile application to fight antibiotic resistance.

Antimicrobial resistance is a major global health threat and its development is promoted by antibiotic misuse. While disk diffusion antibiotic suscept...

Correlation between lung infection severity and clinical laboratory indicators in patients with COVID-19: a cross-sectional study based on machine learning.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has caused a global pandemic that has raised worldwide concern. This study aims to investigate the cor...

Early risk assessment for COVID-19 patients from emergency department data using machine learning.

Since its emergence in late 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic with more than 55 million rep...

Machining learning predicts the need for escalated care and mortality in COVID-19 patients from clinical variables.

This study aimed to develop a machine learning algorithm to identify key clinical measures to triage patients more effectively to general admission v...

HeMA: A hierarchically enriched machine learning approach for managing false alarms in real time: A sepsis prediction case study.

Early detection of sepsis can be life-saving. Machine learning models have shown great promise in early sepsis prediction when applied to patient phys...

DeepAISE - An interpretable and recurrent neural survival model for early prediction of sepsis.

Sepsis, a dysregulated immune system response to infection, is among the leading causes of morbidity, mortality, and cost overruns in the Intensive Ca...

Classification of COVID-19 by Compressed Chest CT Image through Deep Learning on a Large Patients Cohort.

Corona Virus Disease (COVID-19) has spread globally quickly, and has resulted in a large number of causalities and medical resources insufficiency in ...