COVID-19

Evaluation of the bias and precision of regression techniques and machine learning approaches in total dissolved solids modeling of an urban aquifer.

TDS is modeled for an aquifer near an unlined landfill in Canada. Canadian Drinking Water Guidelines and other indices are used to evaluate TDS concentrations in 27 monitoring wells surrounding the landfill. This study aims to predict TDS concentrations using three different modeling approaches: dual-step multiple linear regression (MLR), hybrid principal component regression (PCR), and backpropag...

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning.

We describe here a protocol for the label-free identification of lymphocyte subtypes using quantitative phase imaging and machine learning. Identification of lymphocyte subtypes is important for the study of immunology as well as diagnosis and treatment of various diseases. Currently, standard methods for classifying lymphocyte types rely on labeling specific membrane proteins via antigen-antibody...

MAIA-A machine learning assisted image annotation method for environmental monitoring and exploration.

Digital imaging has become one of the most important techniques in environmental monitoring and exploration. In the case of the marine environment, mo...

Molecular prevalence of parvovirus B19 among HIV1-infected patients in Iran.

Different outcomes of parvovirus B19 (B19V) infection in immunocompromised patients, including HIV1-infected persons, may be life-threatening. Consid...

Machine learning to identify pairwise interactions between specific IgE antibodies and their association with asthma: A cross-sectional analysis within a population-based birth cohort.

BACKGROUND: The relationship between allergic sensitisation and asthma is complex; the data about the strength of this association are conflicting. We...

Robotic hip joint testing: Development and experimental protocols.

The use of robotic systems combined with force sensing is emerging as the gold standard for in vitro biomechanical joint testing, due to the advantage...

Dihydropteroate synthase based sensor for screening multi-sulfonamides residue and its comparison with broad-specific antibody based immunoassay by molecular modeling analysis.

A biosensor that could simultaneously detect multi-analyte as many as in a single test is more favored when facing lots of samples for screening purpo...

A novel nanobody and mimotope based immunoassay for rapid analysis of aflatoxin B1.

Mimotopes could replace mycotoxins and their conjugates to develop immunoassay methods. The mimotopes obtained by phage display technology were mainly...

Anti-microbial and anti-mycotoxigenic activities of endophytic isolated from (L.) G. Don.: molecular characterisation and bioactive compound isolation.

The present study investigated the anti-microbial and anti-mycotoxigenic activities of the ethyl acetate extract (EA) and a bioactive compound obtaine...

A deep learning approach to automate refinement of somatic variant calling from cancer sequencing data.

Cancer genomic analysis requires accurate identification of somatic variants in sequencing data. Manual review to refine somatic variant calls is requ...

Social robots to support children's well-being under medical treatment: A systematic state-of-the-art review.

Hospitalization is a stressful experience for children. Socially assistive robots (SARs), designed to interact with humans, might be a means to mitiga...

Identification of bacteria in juice/lettuce using magnetic nanoparticles and selected reaction monitoring mass spectrometry.

Ensuring food safety requires a rapid and reliable method for detecting food-borne pathogens. Mass spectrometry has been demonstrated as a powerful to...

Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set.

PURPOSE: To determine whether a multivariate machine learning-based model using computer-extracted features of pre-treatment dynamic contrast-enhanced...

An evaluation method of risk grades for prostate cancer using similarity measure of cubic hesitant fuzzy sets.

Prostate cancer (PC) is more common cancer in older men. Then, the existing evaluation method of PC risk grades is based on the AJCC (American Joint C...

Development of a deep residual learning algorithm to screen for glaucoma from fundus photography.

The Purpose of the study was to develop a deep residual learning algorithm to screen for glaucoma from fundus photography and measure its diagnostic p...

[An unusual cause of jaundice].

Hepatic impairment is common during hyperthyroidism. It is most often asymptomatic. Hyperthyroidism revealed by jaundice has been rarely described in ...

Prediction of methionine oxidation risk in monoclonal antibodies using a machine learning method.

Monoclonal antibodies (mAbs) have become a major class of protein therapeutics that target a spectrum of diseases ranging from cancers to infectious d...

A universal SNP and small-indel variant caller using deep neural networks.

Despite rapid advances in sequencing technologies, accurately calling genetic variants present in an individual genome from billions of short, errorfu...

Detection of masses in mammograms using a one-stage object detector based on a deep convolutional neural network.

Several computer aided diagnosis (CAD) systems have been developed for mammography. They are widely used in certain countries such as the U.S. where m...

LCD: A Fast Contrastive Divergence Based Algorithm for Restricted Boltzmann Machine.

Restricted Boltzmann Machine (RBM) is the building block of Deep Belief Nets and other deep learning tools. Fast learning and prediction are both esse...