COVID-19

MetaRNN: differentiating rare pathogenic and rare benign missense SNVs and InDels using deep learning.

Multiple computational approaches have been developed to improve our understanding of genetic variants. However, their ability to identify rare pathogenic variants from rare benign ones is still lacking. Using context annotations and deep learning methods, we present pathogenicity prediction models, MetaRNN and MetaRNN-indel, to help identify and prioritize rare nonsynonymous single nucleotide var...

Peripapillary atrophy classification using CNN deep learning for glaucoma screening.

Glaucoma is the second leading cause of blindness worldwide, and peripapillary atrophy (PPA) is a morphological symptom associated with it. Therefore, it is necessary to clinically detect PPA for glaucoma diagnosis. This study was aimed at developing a detection method for PPA using fundus images with deep learning algorithms to be used by ophthalmologists or optometrists for screening purposes. T...

Identification of blood species based on surface-enhanced Raman scattering spectroscopy and convolutional neural network.

The identification of blood species is of great significance in many aspects such as forensic science, wildlife protection, and customs security and q...

Biodegradable Smart Face Masks for Machine Learning-Assisted Chronic Respiratory Disease Diagnosis.

Utilizing smart face masks to monitor and analyze respiratory signals is a convenient and effective method to give an early warning for chronic respir...

Explanatory classification of CXR images into COVID-19, Pneumonia and Tuberculosis using deep learning and XAI.

Chest X-ray (CXR) images are considered useful to monitor and investigate a variety of pulmonary disorders such as COVID-19, Pneumonia, and Tuberculos...

Visual Information Computing and Processing Model Based on Artificial Neural Network.

This paper analyzes the parallel and serial information processing structure of visual system and proposes a visual information processing model with ...

Deep Learning Approaches for Detection of Breast Adenocarcinoma Causing Carcinogenic Mutations.

Genes are composed of DNA and each gene has a specific sequence. Recombination or replication within the gene base ends in a permanent change in the n...

A Novel Velocity-Based Control in a Sensor Space for Parallel Manipulators.

It is a challenging task to track objects moving along an unknown trajectory. Conventional model-based controllers require detailed knowledge of a rob...

Forest Environmental Carrying Capacity Based on Deep Learning.

In this paper, we proposed an assessment system of forest environmental carrying capacity from many aspects and comprehensively evaluated and predicte...

Spiking Neural P Systems With Enzymes.

The neurotransmitter is a chemical substance that transmits information between neurons. Its metabolic process includes four links: synthesis, storage...

Estimating individual treatment effect on disability progression in multiple sclerosis using deep learning.

Disability progression in multiple sclerosis remains resistant to treatment. The absence of a suitable biomarker to allow for phase 2 clinical trials ...

Deep-Learning to Predict BRCA Mutation and Survival from Digital H&E Slides of Epithelial Ovarian Cancer.

BRCA 1/2 genes mutation status can already determine the therapeutic algorithm of high grade serous ovarian cancer patients. Nevertheless, its assessm...

Deep learning techniques for detecting and recognizing face masks: A survey.

The year 2020 brought many changes to the lives of people all over the world with the outbreak of COVID-19; we saw lockdowns for months and deaths of ...

A deep learning approach to median nerve evaluation in ultrasound images of carpal tunnel inlet.

Ultrasound (US) imaging is recognized as a useful support for Carpal Tunnel Syndrome (CTS) assessment through the evaluation of median nerve morpholog...

Security Analysis of Social Network Topic Mining Using Big Data and Optimized Deep Convolutional Neural Network.

This research aims to conduct topic mining and data analysis of social network security using social network big data. At present, the main problem is...

TaskDrop: A competitive baseline for continual learning of sentiment classification.

In this paper, we study the multi-task sentiment classification problem in the continual learning setting, i.e., a model is sequentially trained to cl...

Application and Communication Optimization Technology of Unmanned Distribution Car under Deep Learning in Logistics Express of COVID-19.

This work aims to solve the problem that the daily necessities of urban residents cannot be delivered during coronavirus disease 2019 (COVID-19), ther...

SVision: a deep learning approach to resolve complex structural variants.

Complex structural variants (CSVs) encompass multiple breakpoints and are often missed or misinterpreted. We developed SVision, a deep-learning-based ...

A digital mask to safeguard patient privacy.

The storage of facial images in medical records poses privacy risks due to the sensitive nature of the personal biometric information that can be extr...

MalFuzz: Coverage-guided fuzzing on deep learning-based malware classification model.

With the continuous development of deep learning, more and more domains use deep learning technique to solve key problems. The security issues of deep...