COVID-19

How to Improve Compliance with Protective Health Measures during the COVID-19 Outbreak: Testing a Moderated Mediation Model and Machine Learning Algorithms.

In the wake of the sudden spread of COVID-19, a large amount of the Italian population practiced incongruous behaviors with the protective health measures. The present study aimed at examining psychological and psychosocial variables that could predict behavioral compliance. An online survey was administered from 18-22 March 2020 to 2766 participants. Paired sample -tests were run to compare effic...

Deep neural network improves the estimation of polygenic risk scores for breast cancer.

Polygenic risk scores (PRS) estimate the genetic risk of an individual for a complex disease based on many genetic variants across the whole genome. In this study, we compared a series of computational models for estimation of breast cancer PRS. A deep neural network (DNN) was found to outperform alternative machine learning techniques and established statistical algorithms, including BLUP, BayesA...

A genotype imputation method for de-identified haplotype reference information by using recurrent neural network.

Genotype imputation estimates the genotypes of unobserved variants using the genotype data of other observed variants based on a collection of haploty...

A multimodal deep learning-based drug repurposing approach for treatment of COVID-19.

Recently, various computational methods have been proposed to find new therapeutic applications of the existing drugs. The Multimodal Restricted Boltz...

Peginterferon and Entecavir Combination Therapy Improves Outcome of Non-Early Response Hepatitis B e Antigen-Positive Patients.

BACKGROUND: The efficacy of nucleot(s)ide analogs (NAs) and pegylated interferon (PegIFN) combination therapy for hepatitis B e antigen-positive (HBeA...

Prognostic machine learning models for COVID-19 to facilitate decision making.

An increasing number of COVID-19 cases worldwide has overwhelmed the healthcare system. Physicians are struggling to allocate resources and to focus t...

BRAVE-NET: Fully Automated Arterial Brain Vessel Segmentation in Patients With Cerebrovascular Disease.

Arterial brain vessel assessment is crucial for the diagnostic process in patients with cerebrovascular disease. Non-invasive neuroimaging techniques...

Diagnosis of Coronavirus Disease 2019 Pneumonia by Using Chest Radiography: Value of Artificial Intelligence.

Background Radiologists are proficient in differentiating between chest radiographs with and without symptoms of pneumonia but have found it more chal...

Improving the performance of CNN to predict the likelihood of COVID-19 using chest X-ray images with preprocessing algorithms.

OBJECTIVE: This study aims to develop and test a new computer-aided diagnosis (CAD) scheme of chest X-ray images to detect coronavirus (COVID-19) infe...

Successful Treatment of Allergic Bronchopulmonary Aspergillosis Using a Combination of Inhaled Fluticasone Furoate/Vilanterol and Oral Voriconazole.

Systemic corticosteroids are considered to be the standard treatment for allergic bronchopulmonary aspergillosis (ABPA). However, there is controversy...

Artificial Intelligence ECG to Detect Left Ventricular Dysfunction in COVID-19: A Case Series.

Coronavirus disease 2019 (COVID-19) can result in deterioration of cardiac function, which is associated with high mortality. A simple point-of-care d...

Amplification Curve Analysis: Data-Driven Multiplexing Using Real-Time Digital PCR.

Information about the kinetics of PCR reactions is encoded in the amplification curve. However, in digital PCR (dPCR), this information is typically n...

Brain tumor segmentation using 3D Mask R-CNN for dynamic susceptibility contrast enhanced perfusion imaging.

The segmentation of neoplasms is an important part of radiotherapy treatment planning, monitoring disease progression, and predicting patient outcome....

Incorporation of Urinary Neutrophil Gelatinase-Associated Lipocalin and Computed Tomography Quantification to Predict Acute Kidney Injury and In-Hospital Death in COVID-19 Patients.

BACKGROUND: The prevalence of acute kidney injury (AKI) in COVID-19 patients is high, with poor prognosis. Early identification of COVID-19 patients w...

Sensitivity analysis based on the random forest machine learning algorithm identifies candidate genes for regulation of innate and adaptive immune response of chicken.

Two categories of immune responses-innate and adaptive immunity-have both polygenic backgrounds and a significant environmental component. The goal of...

SERS-based lateral flow assay combined with machine learning for highly sensitive quantitative analysis of Escherichia coli O157:H7.

In the present study, surface-enhanced Raman scattering-based lateral flow assay (SERS-LFA) strips were applied to promptly and sensitively detect Esc...

Drug Design of Targeted Chemical Libraries Based on Artificial Intelligence and Pair-Based Multiobjective Optimization.

Artificial intelligence and multiobjective optimization represent promising solutions to bridge chemical and biological landscapes by addressing the a...

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...

Identification of the human DPR core promoter element using machine learning.

The RNA polymerase II (Pol II) core promoter is the strategic site of convergence of the signals that lead to the initiation of DNA transcription, but...

MosaicBase: A Knowledgebase of Postzygotic Mosaic Variants in Noncancer Disease-related and Healthy Human Individuals.

Mosaic variants resulting from postzygotic mutations are prevalent in the human genome and play important roles in human diseases. However, except for...