Infectious Disease

Using a simple open-source automated machine learning algorithm to forecast COVID-19 spread: A modelling study.

INTRODUCTION: Machine learning algorithms have been used to develop prediction models in various infectious and non-infectious settings including interpretation of images in predicting the outcome of diseases. We demonstrate the application of one such simple automated machine learning algorithm to a dataset obtained about COVID-19 spread in South Korea to better understand the disease dynamics.

OCCAM: prediction of small ORFs in bacterial genomes by means of a target-decoy database approach and machine learning techniques.

Small open reading frames (ORFs) have been systematically disregarded by automatic genome annotation. The difficulty in finding patterns in tiny sequences is the main reason that makes small ORFs to be overlooked by computational procedures. However, advances in experimental methods show that small proteins can play vital roles in cellular activities. Hence, it is urgent to make progress in the de...

Revisiting CRISPR/Cas-mediated crop improvement: Special focus on nutrition.

Genome editing (GE) technology has emerged as a multifaceted strategy that instantaneously popularised the mechanism to modify the genetic constitutio...

Evaluating the Effect of Dexmedetomidine on Hemodynamic Status of Patients with Septic Shock Admitted to Intensive Care Unit: A Single-Blind Randomized Controlled Trial.

Septic shock, known as the most severe complication of sepsis, is a serious medical condition that can lead to death. Clinical symptoms of sepsis incl...

Comparative Evaluation of Antibacterial Activity of Probiotics SK12 and SM18: An Study.

AIM: To assess the antimicrobial activity of probiotics SK12 and SM18 on and also to compare the antimicrobial activity of SK12 and SM18.

Deep Learning Analysis of Cerebral Blood Flow to Identify Cognitive Impairment and Frailty in Persons Living With HIV.

BACKGROUND: Deep learning algorithms of cerebral blood flow were used to classify cognitive impairment and frailty in people living with HIV (PLWH). F...

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

OBJECTIVE: To use unsupervised topic modeling to evaluate heterogeneity in sepsis treatment patterns contained within granular data of electronic heal...

Lung Segmentation on HRCT and Volumetric CT for Diffuse Interstitial Lung Disease Using Deep Convolutional Neural Networks.

A robust lung segmentation method using a deep convolutional neural network (CNN) was developed and evaluated on high-resolution computed tomography (...

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 that this data type will be the primary one generate...

FRENCH MARIGOLD (TAGETES PATULA L.) FLOWER EXTRACT PROTECTS KIDNEY CELLS FROM INFLAMMATION IN VITRO.

The aim of our study is to evaluate the mechanisms of anti-inflammatory property of Tagetes patula L. (French Marigold) flower extracts and its protec...

PVsiRNAPred: Prediction of plant exclusive virus-derived small interfering RNAs by deep convolutional neural network.

Plant exclusive virus-derived small interfering RNAs (vsiRNAs) regulate various biological processes, especially important in antiviral immunity. The ...

[Severe influenza A (H1N1) in late pregnancy: a case report].

Pregnancy has increased susceptibility to H1N1 influenza virus infection. Maternal influenza infection is associated with increased risk of morbidity ...

Gene-gene interaction: the curse of dimensionality.

Identified genetic variants from genome wide association studies frequently show only modest effects on the disease risk, leading to the "missing heri...

A virus precipitation method for concentration & detection of avian influenza viruses from environmental water resources & its possible application in outbreak investigations.

BACKGROUND & OBJECTIVES: Avian influenza (AI) viruses have been a major cause of public health concern. Wild migratory birds and contaminated environm...

[Usefulness of the CONUT Score for Predicting the Risk of Surgical Site Infections].

BACKGROUND: Surgical site infections(SSIs)occur at a high frequency in patients after rectal cancer surgery and are readily aggravated. Therefore, pro...

Rumex dentatus could be a potent alternative to treatment of microbial infections and of breast cancer.

OBJECTIVE: To investigate the phytochemicals and in vitro antioxidant, antimicrobial and cytotoxic potential of Rumex dentatus (R. dentatus) leaf extr...

Develop machine learning-based regression predictive models for engineering protein solubility.

MOTIVATION: Protein activity is a significant characteristic for recombinant proteins which can be used as biocatalysts. High activity of proteins red...

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 predict severe sepsis and septic shock (Early Warning S...

Network context matters: graph convolutional network model over social networks improves the detection of unknown HIV infections among young men who have sex with men.

OBJECTIVE: HIV infection risk can be estimated based on not only individual features but also social network information. However, there have been ins...

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 shock and evaluate the impact on clinical practice ...