COVID-19

AbAgIntPre: A deep learning method for predicting antibody-antigen interactions based on sequence information.

INTRODUCTION: Antibody-mediated immunity is an essential part of the immune system in vertebrates. The ability to specifically bind to antigens allows antibodies to be widely used in the therapy of cancers and other critical diseases. A key step in antibody therapeutics is the experimental identification of antibody-antigen interactions, which is generally time-consuming, costly, and laborious. Al...

AI support for accurate and fast radiological diagnosis of COVID-19: an international multicenter, multivendor CT study.

OBJECTIVES: Differentiation between COVID-19 and community-acquired pneumonia (CAP) in computed tomography (CT) is a task that can be performed by human radiologists and artificial intelligence (AI). The present study aims to (1) develop an AI algorithm for differentiating COVID-19 from CAP and (2) evaluate its performance. (3) Evaluate the benefit of using the AI result as assistance for radiolog...

Application of Deep Learning on Single-cell RNA Sequencing Data Analysis: A Review.

Single-cell RNA sequencing (scRNA-seq) has become a routinely used technique to quantify the gene expression profile of thousands of single cells simu...

Boosting tissue-specific prediction of active cis-regulatory regions through deep learning and Bayesian optimization techniques.

BACKGROUND: Cis-regulatory regions (CRRs) are non-coding regions of the DNA that fine control the spatio-temporal pattern of transcription; they are i...

Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models.

Antibodies are an established class of human therapeutics. Epitope characterization is an important part of therapeutic antibody discovery. However, s...

Image Translation by Ad CycleGAN for COVID-19 X-Ray Images: A New Approach for Controllable GAN.

We propose a new generative model named adaptive cycle-consistent generative adversarial network, or Ad CycleGAN to perform image translation between ...

Semantic-Powered Explainable Model-Free Few-Shot Learning Scheme of Diagnosing COVID-19 on Chest X-Ray.

Chest X-ray (CXR) is commonly performed as an initial investigation in COVID-19, whose fast and accurate diagnosis is critical. Recently, deep learnin...

Ensemble learning for glioma patients overall survival prediction using pre-operative MRIs.

: Gliomas are the most common primary brain tumors. Approximately 70% of the glioma patients diagnosed with glioblastoma have an averaged overall surv...

Considerations and Challenges for Real-World Deployment of an Acoustic-Based COVID-19 Screening System.

Coronavirus disease 2019 (COVID-19) has led to countless deaths and widespread global disruptions. Acoustic-based artificial intelligence (AI) tools c...

Deep Learning of Dual Plasma Fingerprints for High-Performance Infection Classification.

Infection classification is the key for choosing the proper treatment plans. Early determination of the causative agents is critical for disease contr...

Several machine learning techniques comparison for the prediction of the uniaxial compressive strength of carbonate rocks.

In engineering practices, it is critical and necessary to either measure or estimate the uniaxial compressive strength (UCS) of the rock. Measuring th...

Analyzing factors contributing to COVID-19 mortality in the United States using artificial intelligence techniques.

Having started since late 2019, COVID-19 has spread through far many nations around the globe. Not being known profoundly, the novel virus of the Coro...

An automated, fully-integrated nucleic acid analyzer based on microfluidic liquid handling robot technique.

On-site nucleic acid testing (NAT) plays an important role for disease monitoring and pathogen diagnosis. In this work, we developed an automated and ...

3D CT-Inclusive Deep-Learning Model to Predict Mortality, ICU Admittance, and Intubation in COVID-19 Patients.

Chest CT is a useful initial exam in patients with coronavirus disease 2019 (COVID-19) for assessing lung damage. AI-powered predictive models could b...

Artificial intelligence model with deep learning in nonalcoholic fatty liver disease diagnosis: genetic based artificial neural networks.

Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease in the world. The NAFLD spectrum includes simple st...

Off the deep end: What can deep learning do for the gene expression field?

After a COVID-related hiatus, the fifth biennial symposium on Evolution and Core Processes in Gene Regulation met at the Stowers Institute in Kansas C...

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography.

Recently, deep learning-based segmentation models have been widely applied in the ophthalmic field. This study presents the complete process of constr...

Detection of Green Asparagus Using Improved Mask R-CNN for Automatic Harvesting.

Advancements in deep learning and computer vision have led to the discovery of numerous effective solutions to challenging problems in the field of ag...

Multi-site cross-organ calibrated deep learning (MuSClD): Automated diagnosis of non-melanoma skin cancer.

Although deep learning (DL) has demonstrated impressive diagnostic performance for a variety of computational pathology tasks, this performance often ...

Identification of agricultural quarantine materials in passenger's luggage using ion mobility spectroscopy combined with a convolutional neural network.

As economic globalization intensifies, the recent increase in agricultural products and travelers from abroad has led to an increase in the probabilit...