Infectious Disease

Transforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola Patients.

BACKGROUND: Assessment of the response to the 2014-15 Ebola outbreak indicates the need for innovations in data collection, sharing, and use to improve case detection and treatment. Here we introduce a Machine Learning pipeline for Ebola Virus Disease (EVD) prognosis prediction, which packages the best models into a mobile app to be available in clinical care settings. The pipeline was trained on ...

A new approach to the automatic identification of organism evolution using neural networks.

Automatic identification of organism evolution still remains a challenging task, which is especially exiting, when the evolution of human is considered. The main aim of this work is to present a new idea to allow organism evolution analysis using neural networks. Here we show that it is possible to identify evolution of any organisms in a fully automatic way using the designed EvolutionXXI program...

Hybrid Network Model for "Deep Learning" of Chemical Data: Application to Antimicrobial Peptides.

We present a "deep" network architecture for chemical data analysis and classification together with a prospective proof-of-concept application. The m...

Use of response surface method for maximizing the production of arginine deiminase by .

Statistically designed experiments were used to optimize the production of arginine deiminase (ADI) by KT2440 in batch culture. A Plackett-Burman des...

Simple and Versatile Detection of Viruses Using Anodized Alumina Membranes.

A simple sensor for viral particles based on ionic conductivity through anodized alumina membranes was demonstrated using MS2 bacteriophage as an exam...

Paraconsistents artificial neural networks applied to the study of mutational patterns of the F subtype of the viral strains of HIV-1 to antiretroviral therapy.

The high variability of HIV-1 as well as the lack of efficient repair mechanisms during the stages of viral replication, contribute to the rapid emerg...

Salmonella infections modelling in Mississippi using neural network and geographical information system (GIS).

OBJECTIVES: Mississippi (MS) is one of the southern states with high rates of foodborne infections. The objectives of this paper are to determine the ...

Hierarchical Clustering Multi-Task Learning for Joint Human Action Grouping and Recognition.

This paper proposes a hierarchical clustering multi-task learning (HC-MTL) method for joint human action grouping and recognition. Specifically, we fo...

Vitamin D Deficiency in Obsessive-Compulsive Disorder Patients with Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections: A Case Control Study.

INTRODUCTION: Previous studies have indicated that vitamin D deficiency is common in psychiatric patients, particularly in those with neuropsychiatric...

Two-Swim Operators in the Modified Bacterial Foraging Algorithm for the Optimal Synthesis of Four-Bar Mechanisms.

This paper presents two-swim operators to be added to the chemotaxis process of the modified bacterial foraging optimization algorithm to solve three ...

Vaccine and Drug Ontology Studies (VDOS 2014).

The "Vaccine and Drug Ontology Studies" (VDOS) international workshop series focuses on vaccine- and drug-related ontology modeling and applications. ...

Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast.

Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization o...

Evaluation of a machine learning capability for a clinical decision support system to enhance antimicrobial stewardship programs.

OBJECTIVE: Antimicrobial stewardship programs have been shown to limit the inappropriate use of antimicrobials. Hospitals are increasingly relying on ...

Network stratification analysis for identifying function-specific network layers.

A major challenge of systems biology is to capture the rewiring of biological functions (e.g. signaling pathways) in a molecular network. To address t...

Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity.

Statistical-based and expert rule-based models built using public domain mutagenicity knowledge and data are routinely used for computational (Q)SAR a...

Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.

OBJECTIVES: Predictive analytics in emergency care has mostly been limited to the use of clinical decision rules (CDRs) in the form of simple heuristi...

A Q-backpropagated time delay neural network for diagnosing severity of gait disturbances in Parkinson's disease.

Parkinson's disease (PD) is a movement disorder that affects the patient's nervous system and health-care applications mostly uses wearable sensors to...

Isolation and Identification of Plant Growth Promoting Rhizobacteria from Cucumber Rhizosphere and Their Effect on Plant Growth Promotion and Disease Suppression.

Plant growth promoting rhizobacteria (PGPR) are the rhizosphere bacteria that may be utilized to augment plant growth and suppress plant diseases. The...

Combination of the Manifold Dimensionality Reduction Methods with Least Squares Support vector machines for Classifying the Species of Sorghum Seeds.

This study was carried out for rapid and noninvasive determination of the class of sorghum species by using the manifold dimensionality reduction (MDR...

Antibacterial activities of the methanol extracts of , , and three other Cameroonian plants against multi-drug resistant Gram-negative bacteria.

In the last 10 years, resistance in Gram-negative bacteria has been increasing. The present study was designed to evaluate the antibacterial activiti...