COVID-19

Current Landscape of Imaging and the Potential Role for Artificial Intelligence in the Management of COVID-19.

The clinical management of COVID-19 is challenging. Medical imaging plays a critical role in the early detection, clinical monitoring and outcomes assessment of this disease. Chest x-ray radiography and computed tomography) are the standard imaging modalities used for the structural assessment of the disease status, while functional imaging (namely, positron emission tomography) has had limited ap...

The Future of Skull Base Surgery: A View Through Tinted Glasses.

In the present report, we have broadly outlined the potential advances in the field of skull base surgery, which might occur within the next 20 years based on the many areas of current research in biology and technology. Many of these advances will also be broadly applicable to other areas of neurosurgery. We have grounded our predictions for future developments in an exploration of what patients ...

New machine learning method for image-based diagnosis of COVID-19.

COVID-19 is a worldwide epidemic, as announced by the World Health Organization (WHO) in March 2020. Machine learning (ML) methods can play vital role...

Immunopeptidomic Data Integration to Artificial Neural Networks Enhances Protein-Drug Immunogenicity Prediction.

Recombinant DNA technology has, in the last decades, contributed to a vast expansion of the use of protein drugs as pharmaceutical agents. However, su...

Explainable Deep Learning for Pulmonary Disease and Coronavirus COVID-19 Detection from X-rays.

BACKGROUND AND OBJECTIVE: Coronavirus disease (COVID-19) is an infectious disease caused by a new virus never identified before in humans. This virus ...

Spatio-temporal visual attention modelling of standard biometry plane-finding navigation.

We present a novel multi-task neural network called Temporal SonoEyeNet (TSEN) with a primary task to describe the visual navigation process of sonogr...

Appearance variation adaptation tracker using adversarial network.

Visual trackers using deep neural networks have demonstrated favorable performance in object tracking. However, training a deep classification network...

CIDO, a community-based ontology for coronavirus disease knowledge and data integration, sharing, and analysis.

The Coronavirus Infectious Disease Ontology (CIDO) is a community-based ontology that supports coronavirus disease knowledge and data standardization,...

Artificial Neural Network Modeling of Novel Coronavirus (COVID-19) Incidence Rates across the Continental United States.

Prediction of the COVID-19 incidence rate is a matter of global importance, particularly in the United States. As of 4 June 2020, more than 1.8 millio...

Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment.

COVID-19 outbreak has put the whole world in an unprecedented difficult situation bringing life around the world to a frightening halt and claiming th...

R-ELMNet: Regularized extreme learning machine network.

Principal component analysis network (PCANet), as an unsupervised shallow network, demonstrates noticeable effectiveness on datasets of various volume...

Differentiating molecular etiologies of Angelman syndrome through facial phenotyping using deep learning.

Angelman syndrome (AS) is caused by several genetic mechanisms that impair the expression of maternally-inherited UBE3A through deletions, paternal un...

Machine-learning-based diagnostics of EEG pathology.

Machine learning (ML) methods have the potential to automate clinical EEG analysis. They can be categorized into feature-based (with handcrafted featu...

Artificial-intelligence tools aim to tame the coronavirus literature.

Efficient GAN-based Chest Radiographs (CXR) augmentation to diagnose coronavirus disease pneumonia.

: As 2019 ends coronavirus disease start expanding all over the world. It is highly transmissible disease that can affect respiratory tract and can le...

CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images.

BACKGROUND AND OBJECTIVE: The novel Coronavirus also called COVID-19 originated in Wuhan, China in December 2019 and has now spread across the world. ...

Risk of a second wave of Covid-19 infections: using artificial intelligence to investigate stringency of physical distancing policies in North America.

PURPOSE: Accurately forecasting the occurrence of future covid-19-related cases across relaxed (Sweden) and stringent (USA and Canada) policy contexts...

Major Depressive Disorder Classification Based on Different Convolutional Neural Network Models: Deep Learning Approach.

The human brain is characterized by complex structural, functional connections that integrate unique cognitive characteristics. There is a fundamental...

COVID-19: The role of artificial intelligence in empowering the healthcare sector and enhancing social distancing measures during a pandemic.

Indiscriminatory in its spread, COVID-19 has engulfed communities from all social backgrounds throughout the world. While healthcare professionals wor...

Envisioning Insight-Driven Learning Based on Thick Data Analytics With Focus on Healthcare.

Detecting and analyzing patient insights from social media enables healthcare givers to better understand what patients want and also to identify thei...