COVID-19

Automated Molecular Subtyping of Breast Carcinoma Using Deep Learning Techniques.

OBJECTIVE: Molecular subtyping is an important procedure for prognosis and targeted therapy of breast carcinoma, the most common type of malignancy affecting women. Immunohistochemistry (IHC) analysis is the widely accepted method for molecular subtyping. It involves the assessment of the four molecular biomarkers namely estrogen receptor (ER), progesterone receptor (PR), human epidermal growth fa...

DapNet-HLA: Adaptive dual-attention mechanism network based on deep learning to predict non-classical HLA binding sites.

Human leukocyte antigen (HLA) plays a vital role in immunomodulatory function. Studies have shown that immunotherapy based on non-classical HLA has essential applications in cancer, COVID-19, and allergic diseases. However, there are few deep learning methods to predict non-classical HLA alleles. In this work, an adaptive dual-attention network named DapNet-HLA is established based on existing dat...

Knowledge Sharing for Pulmonary Nodule Detection in Medical Cyber-Physical Systems.

With the rapid development of edge intelligence (EI) and machine learning (ML), the applications of Cyber-Physical Systems (CPS) have been discovered ...

CXR-Net: A Multitask Deep Learning Network for Explainable and Accurate Diagnosis of COVID-19 Pneumonia From Chest X-Ray Images.

Accurate and rapid detection of COVID-19 pneumonia is crucial for optimal patient treatment. Chest X-Ray (CXR) is the first-line imaging technique for...

Artificial Intelligence-Driven Image Analysis of Bacterial Cells and Biofilms.

The current study explores an artificial intelligence framework for measuring the structural features from microscopy images of the bacterial biofilms...

Noise Reduction Learning Based on XLNet-CRF for Biomedical Named Entity Recognition.

In recent years, Biomedical Named Entity Recognition (BioNER) systems have mainly been based on deep neural networks, which are used to extract inform...

Socially assistive robots in health and social care: Acceptance and cultural factors. Results from an exploratory international online survey.

AIM: This study explored the views of an international sample of registered nurses and midwives working in health and social care concerning socially ...

Biologically informed deep learning to query gene programs in single-cell atlases.

The increasing availability of large-scale single-cell atlases has enabled the detailed description of cell states. In parallel, advances in deep lear...

Simultaneous Segmentation and Classification of Pressure Injury Image Data Using Mask-R-CNN.

BACKGROUND: Pressure injuries (PIs) impose a substantial burden on patients, caregivers, and healthcare systems, affecting an estimated 3 million Amer...

Socioexposomics of COVID-19 across New Jersey: a comparison of geostatistical and machine learning approaches.

BACKGROUND: Disparities in adverse COVID-19 health outcomes have been associated with multiple social and environmental stressors. However, research i...

Explainable artificial intelligence model for identifying COVID-19 gene biomarkers.

AIM: COVID-19 has revealed the need for fast and reliable methods to assist clinicians in diagnosing the disease. This article presents a model that a...

MaskID: An effective deep-learning-based algorithm for dense rebar counting.

As a dense instance segmentation problem, rebar counting in a complex environment such as rebar yard and rebar transpotation has received significant ...

IGPred-HDnet: Prediction of Immunoglobulin Proteins Using Graphical Features and the Hierarchal Deep Learning-Based Approach.

. Immunoglobulin proteins (IGP) (also called antibodies) are glycoproteins that act as B-cell receptors against external or internal antigens like vir...

Classification of COVID-19 from community-acquired pneumonia: Boosting the performance with capsule network and maximum intensity projection image of CT scans.

BACKGROUND: The coronavirus disease 2019 (COVID-19) and community-acquired pneumonia (CAP) present a high degree of similarity in chest computed tomog...

COVID-19 Classification on Chest X-ray Images Using Deep Learning Methods.

Since December 2019, the coronavirus disease has significantly affected millions of people. Given the effect this disease has on the pulmonary systems...

Current Role of Delta Radiomics in Head and Neck Oncology.

The latest developments in the management of head and neck cancer show an increasing trend in the implementation of novel approaches using artificial ...

Comparison of the Diagnostic Performance of Deep Learning Algorithms for Reducing the Time Required for COVID-19 RT-PCR Testing.

(1) Background: Rapid and accurate negative discrimination enables efficient management of scarce isolated bed resources and adequate patient accommod...

An automated, low volume, and high-throughput analytical platform for aggregate quantitation from cell culture media.

High throughput screening methods have driven a paradigm shift in biopharmaceutical development by reducing the costs of good manufactured (COGM) and ...

Prediction of pathologic complete response to neoadjuvant systemic therapy in triple negative breast cancer using deep learning on multiparametric MRI.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. Neoadjuvant systemic therapy (NAST) followed by surgery are currently ...

Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics.

Generating and analyzing overlapping peptides through multienzymatic digestion is an efficient procedure for de novo protein using from bottom-up mass...