Infectious Disease

Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations.

Structure prediction for proteins lacking homologous templates in the Protein Data Bank (PDB) remains a significant unsolved problem. We developed a protocol, C-I-TASSER, to integrate interresidue contact maps from deep neural-network learning with the cutting-edge I-TASSER fragment assembly simulations. Large-scale benchmark tests showed that C-I-TASSER can fold more than twice the number of non-...

Deep learning for classification of pediatric chest radiographs by WHO's standardized methodology.

BACKGROUND: The World Health Organization (WHO)-defined radiological pneumonia is a preferred endpoint in pneumococcal vaccine efficacy and effectiveness studies in children. Automating the WHO methodology may support more widespread application of this endpoint.

BARD: A Structured Technique for Group Elicitation of Bayesian Networks to Support Analytic Reasoning.

In many complex, real-world situations, problem solving and decision making require effective reasoning about causation and uncertainty. However, huma...

Deep learning-based framework for the distinction of membranous nephropathy: a new approach through hyperspectral imagery.

BACKGROUND: Common subtypes seen in Chinese patients with membranous nephropathy (MN) include idiopathic membranous nephropathy (IMN) and hepatitis B ...

Predicting malaria epidemics in Burkina Faso with machine learning.

Accurately forecasting the case rate of malaria would enable key decision makers to intervene months before the onset of any outbreak, potentially sav...

Detecting COVID-19 in Chest X-Ray Images via MCFF-Net.

COVID-19 is a respiratory disease caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2). Due to the rapid spread of COVID-19 around the...

Speech signal enhancement in cocktail party scenarios by deep learning based virtual sensing of head-mounted microphones.

The cocktail party effect refers to the human sense of hearing's ability to pay attention to a single conversation while filtering out all other backg...

COVID-19 cough classification using machine learning and global smartphone recordings.

We present a machine learning based COVID-19 cough classifier which can discriminate COVID-19 positive coughs from both COVID-19 negative and healthy ...

Deep learning of HIV field-based rapid tests.

Although deep learning algorithms show increasing promise for disease diagnosis, their use with rapid diagnostic tests performed in the field has not ...

A Pragmatic Machine Learning Model To Predict Carbapenem Resistance.

Infection caused by carbapenem-resistant (CR) organisms is a rising problem in the United States. While the risk factors for antibiotic resistance are...

Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection.

High-throughput, high-accuracy detection of emerging viruses allows for the control of disease outbreaks. Currently, reverse transcription-polymerase ...

Multivariable mortality risk prediction using machine learning for COVID-19 patients at admission (AICOVID).

In Coronavirus disease 2019 (COVID-19), early identification of patients with a high risk of mortality can significantly improve triage, bed allocatio...

One-step-immunoassay of procalcitonin enables rapid and accurate diagnosis of bacterial infection.

Procalcitonin (PCT) ( a precursor of calcitonin) attracts much attention as a reliable biomarker of bacterial infections because its concentration inc...

Distinguishing nontuberculous mycobacteria from Mycobacterium tuberculosis lung disease from CT images using a deep learning framework.

PURPOSE: To develop and evaluate the effectiveness of a deep learning framework (3D-ResNet) based on CT images to distinguish nontuberculous mycobacte...

Application of the random forest algorithm to Streptococcus pyogenes response regulator allele variation: from machine learning to evolutionary models.

Group A Streptococcus (GAS) is a globally significant bacterial pathogen. The GAS genotyping gold standard characterises the nucleotide variation of e...

Effectiveness of Tenofovir Alafenamide in Chronic Hepatitis B Patients with Normal Alanine Aminotransferase and Positive Hepatitis B Virus DNA.

BACKGROUND AND AIMS: With an increasing understanding of hepatitis B, the antiviral indications have been broadening gradually. To evaluate the effect...

Deep convolutional neural networks for COVID-19 automatic diagnosis.

This article is mainly concerned with COVID-19 diagnosis from X-ray images. The number of cases infected with COVID-19 is increasing daily, and there ...

Real-time Prediction of the Daily Incidence of COVID-19 in 215 Countries and Territories Using Machine Learning: Model Development and Validation.

BACKGROUND: Advanced prediction of the daily incidence of COVID-19 can aid policy making on the prevention of disease spread, which can profoundly aff...

Using deep learning to identify recent positive selection in malaria parasite sequence data.

BACKGROUND: Malaria, caused by Plasmodium parasites, is a major global public health problem. To assist an understanding of malaria pathogenesis, incl...

A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections.

PURPOSE: Accurate segmentation of brain resection cavities (RCs) aids in postoperative analysis and determining follow-up treatment. Convolutional neu...