Infectious Disease

Using Machine Learning to Generate Novel Hypotheses: Increasing Optimism About COVID-19 Makes People Less Willing to Justify Unethical Behaviors.

How can we nudge people to not engage in unethical behaviors, such as hoarding and violating social-distancing guidelines, during the COVID-19 pandemic? Because past research on antecedents of unethical behavior has not provided a clear answer, we turned to machine learning to generate novel hypotheses. We trained a deep-learning model to predict whether or not World Values Survey respondents perc...

Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning.

It is important that antibiotics prescriptions are based on antimicrobial susceptibility data to ensure effective treatment outcomes. The increasing availability of next-generation sequencing, bacterial whole genome sequencing (WGS) can facilitate a more reliable and faster alternative to traditional phenotyping for the detection and surveillance of AMR. This work proposes a machine learning appro...

Supervised classification techniques for prediction of mortality in adult patients with sepsis.

BACKGROUND: Sepsis mortality is still unacceptably high and an appropriate prognostic tool may increase the accuracy for clinical decisions.

Helping the Blind to Get through COVID-19: Social Distancing Assistant Using Real-Time Semantic Segmentation on RGB-D Video.

The current COVID-19 pandemic is having a major impact on our daily lives. Social distancing is one of the measures that has been implemented with the...

Convolutional Neural Network Based Approach to in Silico Non-Anticipating Prediction of Antigenic Distance for Influenza Virus.

Evaluation of the antigenic similarity degree between the strains of the influenza virus is highly important for vaccine production. The conventional ...

A new advanced in silico drug discovery method for novel coronavirus (SARS-CoV-2) with tensor decomposition-based unsupervised feature extraction.

BACKGROUND: COVID-19 is a critical pandemic that has affected human communities worldwide, and there is an urgent need to develop effective drugs. Alt...

India nudges to contain COVID-19 pandemic: A reactive public policy analysis using machine-learning based topic modelling.

India locked down 1.3 billion people on March 25, 2020, in the wake of COVID-19 pandemic. The economic cost of it was estimated at USD 98 billion, whi...

Training Radiology Residents, Bloom Style.

Bloom's Taxonomy, an integral component of learning theory since its inception, describes cognitive skill levels in increasing complexity (Remember, U...

Ontology and values anchor indigenous and grey nomenclatures: a case study in lichen naming practices among the Samí, Sherpa, Scots, and Okanagan.

Ethnobotanical research provides ample justification for comparing diverse biological nomenclatures and exploring ways that retain alternative naming ...

Machine Learning Strategy for Gut Microbiome-Based Diagnostic Screening of Cardiovascular Disease.

Cardiovascular disease (CVD) is the number one leading cause for human mortality. Besides genetics and environmental factors, in recent years, gut mic...

Estimating the Binding of Sars-CoV-2 Peptides to HLA Class I in Human Subpopulations Using Artificial Neural Networks.

Epidemiological studies show that SARS-CoV-2 infection leads to severe symptoms only in a fraction of patients, but the determinants of individual sus...

Contrastive Cross-Site Learning With Redesigned Net for COVID-19 CT Classification.

The pandemic of coronavirus disease 2019 (COVID-19) has lead to a global public health crisis spreading hundreds of countries. With the continuous gro...

Unsupervised Clustering of Missense Variants in HNF1A Using Multidimensional Functional Data Aids Clinical Interpretation.

Exome sequencing in diabetes presents a diagnostic challenge because depending on frequency, functional impact, and genomic and environmental contexts...

Real-World Implications of a Rapidly Responsive COVID-19 Spread Model with Time-Dependent Parameters via Deep Learning: Model Development and Validation.

BACKGROUND: The COVID-19 pandemic has caused major disruptions worldwide since March 2020. The experience of the 1918 influenza pandemic demonstrated ...

Mimicry Embedding Facilitates Advanced Neural Network Training for Image-Based Pathogen Detection.

The use of deep neural networks (DNNs) for analysis of complex biomedical images shows great promise but is hampered by a lack of large verified data ...

Development of machine learning-based clinical decision support system for hepatocellular carcinoma.

There is a significant discrepancy between the actual choice for initial treatment option for hepatocellular carcinoma (HCC) and recommendations from ...

Incomplete multi-view gene clustering with data regeneration using Shape Boltzmann Machine.

Deciphering patterns in the structural and functional anatomy of genes can prove to be very helpful in understanding genetic biology and genomics. Als...

Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective.

The simultaneous maturation of multiple digital and telecommunications technologies in 2020 has created an unprecedented opportunity for ophthalmology...

Hydroxyl Radical Generation Through the Fenton-Like Reaction of Hematin- and Catechol-Functionalized Microgels.

Hydroxyl radical (OH) is a potent reactive oxygen species with the ability to degrade hazardous organic compounds, kill bacteria, and inactivate virus...

Sequence-enabled community-based microbial source tracking in surface waters using machine learning classification: A review.

The development of Microbial Source Tracking (MST) technologies was borne out of necessity. This was largely due to the: 1) inadequacies of the fecal ...