Universal precautions

Target-Specific Prediction of Ligand Affinity with Structure-Based Interaction Fingerprints.

Discovery and optimization of small molecule inhibitors as therapeutic drugs have immensely benefited from rational structure-based drug design. With recent advances in high-resolution structure determination, computational power, and machine learning methodology, it is becoming more tractable to elucidate the structural basis of drug potency. However, the applicability of machine learning models ...

Cytokeratin-Supervised Deep Learning for Automatic Recognition of Epithelial Cells in Breast Cancers Stained for ER, PR, and Ki-67.

Immunohistochemistry (IHC) of ER, PR, and Ki-67 are routinely used assays in breast cancer diagnostics. Determination of the proportion of stained cells (labeling index) should be restricted on malignant epithelial cells, carefully avoiding tumor infiltrating stroma and inflammatory cells. Here, we developed a deep learning based digital mask for automated epithelial cell detection using fluoro-ch...

Biocide susceptibilities and biofilm-forming capacities of Acinetobacter baumannii clinical isolates from Malaysia.

INTRODUCTION: Acinetobacter baumannii is a Gram-negative nosocomial pathogen that has the capacity to develop resistance to all classes of antimicrobi...

Region-of-interest undersampled MRI reconstruction: A deep convolutional neural network approach.

Compressive sensing enables fast magnetic resonance imaging (MRI) reconstruction with undersampled k-space data. However, in most existing MRI reconst...

Validation of a simple equation for glomerular filtration rate measurement based on plasma iohexol disappearance.

BACKGROUND: A simple equation for glomerular filtration rate (GFR) measurement based on only plasma samples during the slow compartment after injectio...

Targeting HIV/HCV Coinfection Using a Machine Learning-Based Multiple Quantitative Structure-Activity Relationships (Multiple QSAR) Method.

Human immunodeficiency virus type-1 and hepatitis C virus (HIV/HCV) coinfection occurs when a patient is simultaneously infected with both human immun...

Noninvasive Evaluation of Liver Fibrosis Reverse Using Artificial Neural Network Model for Chronic Hepatitis B Patients.

The diagnostic performance of an artificial neural network model for chronic HBV-induced liver fibrosis reverse is not well established. Our research ...

Optical screening of hepatitis-B infected blood sera using optical technique and neural network classifier.

In this study we demonstrate the analysis of biochemical changes in the human blood sera infected with Hepatitis B virus (HBV) using Raman spectroscop...

Utilizing hybrid functional fuzzy wavelet neural networks with a teaching learning-based optimization algorithm for medical disease diagnosis.

Accurate medical disease diagnosis is considered to be an important classification problem. The main goal of the classification process is to determin...

A Ligand-Based Virtual Screening Method Using Direct Quantification of Generalization Ability.

Machine learning plays an important role in ligand-based virtual screening. However, conventional machine learning approaches tend to be inefficient w...

mSphere of Influence: the Rise of Artificial Intelligence in Infection Biology.

Artur Yakimovich works in the field of computational virology and applies machine learning algorithms to study host-pathogen interactions. In this mSp...

Accurate and cost-effective prediction of HBsAg titer in industrial scale fermentation process of recombinant Pichia pastoris by using neural network based soft sensor.

In the current work, the attempt was made to apply best-fitted artificial neural network (ANN) architecture and the respective training process for pr...

Using Machine Learning Algorithms to Predict Hepatitis B Surface Antigen Seroclearance.

Hepatitis B surface antigen (HBsAg) seroclearance during treatment is associated with a better prognosis among patients with chronic hepatitis B (CHB)...

A review on recent advances in soft surgical robots for endoscopic applications.

BACKGROUND: Soft materials, with their compliant properties, enable conformity and safe interaction with human body. With the advance in actuation and...

Error Tolerance of Machine Learning Algorithms across Contemporary Biological Targets.

Machine learning continues to make strident advances in the prediction of desired properties concerning drug development. Problematically, the efficac...

BoSR: A CNN-based aurora image retrieval method.

The deep learning models especially the CNN have achieved amazing performance on natural image retrieval. However, remote sensing images captured with...

Modelling the influence of environmental parameters over marine planktonic microbial communities using artificial neural networks.

Guanabara Bay is a tropical estuarine ecosystem that receives massive anthropogenic impacts from the metropolitan region of Rio de Janeiro. This ecosy...

Machine-Learning-Based Predictor of Human-Bacteria Protein-Protein Interactions by Incorporating Comprehensive Host-Network Properties.

The large-scale identification of protein-protein interactions (PPIs) between humans and bacteria remains a crucial step in systematically understandi...

Qualification of a chemotherapy-compounding robot.

KIRO® Oncology (Kiro Grifols, Spain) is a robotic system for automated compounding of sterile injectable drugs including intravenous cytotoxic treatme...

Quantitative Prediction of the Landscape of T Cell Epitope Immunogenicity in Sequence Space.

Immunodominant T cell epitopes preferentially targeted in multiple individuals are the critical element of successful vaccines and targeted immunother...