COVID-19

Design and development of a social assistive robot for music and game activities: a case study in a residential facility for disabled people.

Cognitive disability strongly reduces people's autonomy in performing desired as well as daily activities. The use of Social Assistive Robots (SARs) for cognitive rehabilitation therapy for disabled people could be a valuable gateway for the residential facility of the future. In this work, we design and develop a SAR that can be used for cognitive therapy proposing music and game activities. The ...

NLP-Assisted Pipeline for COVID-19 Core Outcome Set Identification Using ClinicalTrials.gov.

Core outcome sets (COS) are necessary to ensure the systematic collection, metadata analysis and sharing the information across studies. However, development of an area-specific clinical research is costly and time consuming. ClinicalTrials.gov, as a public repository, provides access to a vast collection of clinical trials and their characteristics such as primary outcomes. With the growing numbe...

The Pitfalls of Using Open Data to Develop Deep Learning Solutions for COVID-19 Detection in Chest X-Rays.

Since the emergence of COVID-19, deep learning models have been developed to identify COVID-19 from chest X-rays. With little to no direct access to h...

Open set classification strategies for long-term environmental field recordings for bird species recognition.

Deep learning is one established tool for carrying out classification tasks on complex, multi-dimensional data. Since audio recordings contain a frequ...

The First Introduction of Social Robotics in Rehabilitation Care.

Can you imagine to receive treatment through a robot? When talking about the future of healthcare, this is the vision many people have. Currently, the...

deepNEC: a novel alignment-free tool for the identification and classification of nitrogen biochemical network-related enzymes using deep learning.

Nitrogen is essential for life and its transformations are an important part of the global biogeochemical cycle. Being an essential nutrient, nitrogen...

Long COVID and cardiovascular disease: a learning health system approach.

Cardiovascular disease is both a risk factor and potential outcome of the direct, indirect and long-term effects of COVID-19. A recent analysis in >15...

[Two Cases of Robot-Assisted Total Pelvic Exenteration and Intracorporeal Ileal Conduit for Locally Advanced Rectal Cancer].

We describe two cases of locally advanced rectal cancer (LARC) treated with robot-assisted total pelvic exenteration (Ra-TPE) and intracorporeal ileal...

Image reconstruction with transformer for mask-based lensless imaging.

A mask-based lensless camera optically encodes the scene with a thin mask and reconstructs the image afterward. The improvement of image reconstructio...

Machine Learning Prediction of Non-Coding Variant Impact in Human Retinal cis-Regulatory Elements.

PURPOSE: Prior studies have demonstrated the significance of specific cis-regulatory variants in retinal disease; however, determining the functional ...

The Delta Robot-A long travel nano-positioning stage for scanning x-ray microscopy.

A new stage design concept, the Delta Robot, is presented, which is a parallel kinematic design for scanning x-ray microscopy applications. The stage ...

CapsNet-COVID19: Lung CT image classification method based on CapsNet model.

The outbreak of the Corona Virus Disease 2019 (COVID-19) has posed a serious threat to human health and life around the world. As the number of COVID-...

SVPath: an accurate pipeline for predicting the pathogenicity of human exon structural variants.

Although there are a large number of structural variations in the chromosomes of each individual, there is a lack of more accurate methods for identif...

Deep learning-based identification of genetic variants: application to Alzheimer's disease classification.

Deep learning is a promising tool that uses nonlinear transformations to extract features from high-dimensional data. Deep learning is challenging in ...

DeepSVP: integration of genotype and phenotype for structural variant prioritization using deep learning.

MOTIVATION: Structural genomic variants account for much of human variability and are involved in several diseases. Structural variants are complex an...

Computational anti-COVID-19 drug design: progress and challenges.

Vaccines have made gratifying progress in preventing the 2019 coronavirus disease (COVID-19) pandemic. However, the emergence of variants, especially ...

Heavy chain sequence-based classifier for the specificity of human antibodies.

Antibodies specifically bind to antigens and are an essential part of the immune system. Hence, antibodies are powerful tools in research and diagnost...

Active disease-related compound identification based on capsule network.

Pneumonia, especially corona virus disease 2019 (COVID-19), can lead to serious acute lung injury, acute respiratory distress syndrome, multiple organ...

DLAB: deep learning methods for structure-based virtual screening of antibodies.

MOTIVATION: Antibodies are one of the most important classes of pharmaceuticals, with over 80 approved molecules currently in use against a wide varie...

An Efficient Method for Coronavirus Detection Through X-rays Using Deep Neural Network.

BACKGROUND: Coronavirus (COVID-19) is a group of infectious diseases caused by related viruses called coronaviruses. In humans, the seriousness of inf...