Devices and Vaccines

An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study.

The rampant spread of COVID-19, an infectious disease caused by SARS-CoV-2, all over the world has led to over millions of deaths, and devastated the social, financial and political entities around the world. Without an existing effective medical therapy, vaccines are urgently needed to avoid the spread of this disease. In this study, we propose an in silico deep learning approach for prediction a...

Emotion Recognition Based on Skin Potential Signals with a Portable Wireless Device.

Emotion recognition is of great importance for artificial intelligence, robots, and medicine etc. Although many techniques have been developed for emotion recognition, with certain successes, they rely heavily on complicated and expensive equipment. Skin potential (SP) has been recognized to be correlated with human emotions for a long time, but has been largely ignored due to the lack of systemat...

Diagnosis of COVID-19 using CT scan images and deep learning techniques.

Early diagnosis of the coronavirus disease in 2019 (COVID-19) is essential for controlling this pandemic. COVID-19 has been spreading rapidly all over...

Machine learning method for predicting pacemaker implantation following transcatheter aortic valve replacement.

BACKGROUND: An accurate assessment of permanent pacemaker implantation (PPI) risk following transcatheter aortic valve replacement (TAVR) is important...

Prediction of adverse drug reactions using drug convolutional neural networks.

Prediction of Adverse Drug Reactions (ADRs) has been an important aspect of Pharmacovigilance because of its impact in the pharma industry. The standa...

Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015-20): a comparative analysis.

There has been a surge of interest in artificial intelligence and machine learning (AI/ML)-based medical devices. However, it is poorly understood how...

Use of machine learning to identify a T cell response to SARS-CoV-2.

The identification of SARS-CoV-2-specific T cell receptor (TCR) sequences is critical for understanding T cell responses to SARS-CoV-2. Accordingly, w...

Empirically constrained network models for contrast-dependent modulation of gamma rhythm in V1.

Gamma oscillations are thought to play a key role in neuronal network function and neuronal communication, yet the underlying generating mechanisms ha...

Foveal avascular zone segmentation in optical coherence tomography angiography images using a deep learning approach.

The purpose of this study was to introduce a new deep learning (DL) model for segmentation of the fovea avascular zone (FAZ) in en face optical cohere...

A Novel Protein Mapping Method for Predicting the Protein Interactions in COVID-19 Disease by Deep Learning.

The new type of corona virus (SARS-COV-2) emerging in Wuhan, China has spread rapidly to the world and has become a pandemic. In addition to having a ...

Total knee arthroplasty: Latest robotics implantation techniques.

The recent introduction of new robotic systems for total knee arthroplasty (TKA) has created somewhat of a craze. Nevertheless, we can ask ourselves w...

Learning Spatiotemporal Features for Esophageal Abnormality Detection From Endoscopic Videos.

Esophageal cancer is categorized as a type of disease with a high mortality rate. Early detection of esophageal abnormalities (i.e. precancerous and e...

Application of Artificial Intelligence to Address Issues Related to the COVID-19 Virus.

Artificial intelligence (AI) plays a major role in addressing novel coronavirus 2019 (COVID-19)-related issues and is also used in computer-aided synt...

Artificial Intelligence Model of Drive-Through Vaccination Simulation.

Planning for mass vaccination against SARS-Cov-2 is ongoing in many countries considering that vaccine will be available for the general public in the...

On-Device Reliability Assessment and Prediction of Missing Photoplethysmographic Data Using Deep Neural Networks.

Photoplethysmographic (PPG) measurements from ambulatory subjects may suffer from unreliability due to body movements and missing data segments due to...

A Head-to Head Comparison of Machine Learning Algorithms for Identification of Implanted Cardiac Devices.

Application of artificial intelligence techniques in medicine has rapidly expanded in recent years. Two algorithms for identification of cardiac impla...

Design of novel orotransmucosal vaccine-delivery platforms using artificial intelligence.

The linings of the oral cavity are excellent needle-free vaccination sites, able to induce immune responses at distal sites and confer systemic protec...

Ultrashort echo time time-spatial labeling inversion pulse magnetic resonance angiography with denoising deep learning reconstruction for the assessment of abdominal visceral arteries.

Current contrast-enhanced magnetic resonance angiography (MRA) and non-contrast-enhanced balanced steady-state free precession (bSSFP) MRA cause susce...

Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2 leading to universal blueprints for vaccine designs.

The global population is at present suffering from a pandemic of Coronavirus disease 2019 (COVID-19), caused by the novel coronavirus Severe Acute Res...

Automated White Blood Cell Counting in Nailfold Capillary Using Deep Learning Segmentation and Video Stabilization.

White blood cells (WBCs) are essential components of the immune system in the human body. Various invasive and noninvasive methods to monitor the cond...