Devices and Vaccines

Applying Convolutional Neural Networks to Predict the ICD-9 Codes of Medical Records.

The International Statistical Classification of Disease and Related Health Problems (ICD) is an international standard system for categorizing and reporting diseases, injuries, disorders, and health conditions. Most previously-proposed disease predicting systems need clinical information collected by the medical staff from the patients in hospitals. In this paper, we propose a deep learning algori...

Hepatitis C viral load and genotypes among Nigerian subjects with chronic infection and implication for patient management: a retrospective review of data.

INTRODUCTION: Hepatitis C Virus (HCV) is highly infectious with no currently available vaccine. Prior to treatment, it is recommended to confirm HCV infection with either quantitative or qualitative nucleic acid test. Access to these assays in Nigeria is limited but for effective management of patients, HCV viral load (VL) prior to therapy is required and genotype may be needed in some instances. ...

NMDA Receptor Alterations After Mild Traumatic Brain Injury Induce Deficits in Memory Acquisition and Recall.

Mild traumatic brain injury (mTBI) presents a significant health concern with potential persisting deficits that can last decades. Although a growing ...

Detection and Localization of Ultrasound Scatterers Using Convolutional Neural Networks.

Delay-and-sum (DAS) beamforming is unable to identify individual scatterers when their density is so high that their point spread functions overlap. T...

Essential gene prediction using limited gene essentiality information-An integrative semi-supervised machine learning strategy.

Essential gene prediction helps to find minimal genes indispensable for the survival of any organism. Machine learning (ML) algorithms have been usefu...

Statistical stopping criteria for automated screening in systematic reviews.

Active learning for systematic review screening promises to reduce the human effort required to identify relevant documents for a systematic review. M...

Predicted Cellular Immunity Population Coverage Gaps for SARS-CoV-2 Subunit Vaccines and Their Augmentation by Compact Peptide Sets.

Subunit vaccines induce immunity to a pathogen by presenting a component of the pathogen and thus inherently limit the representation of pathogen pept...

Accuracy of dental implant surgery with robotic position feedback and registration algorithm: An in-vitro study.

BACKGROUND: The purpose of this study was to develop and validate a positioning method with hand-guiding and contact position feedback of robot based ...

Identification and validation of 174 COVID-19 vaccine candidate epitopes reveals low performance of common epitope prediction tools.

The outbreak of SARS-CoV-2 (2019-nCoV) virus has highlighted the need for fast and efficacious vaccine development. Stimulation of a proper immune res...

Artificial Intelligence, Machine Learning and Calculation of Intraocular Lens Power.

BACKGROUND AND PURPOSE: In the last decade, artificial intelligence and machine learning algorithms have been more and more established for the screen...

Machine Learning Approaches to Analyzing Adverse Events Following Durable LVAD Implantation.

BACKGROUND: This study employed machine learning approaches to analyze sequences of adverse events (AEs) after left ventricular assist device (LVAD) i...

Predictive score for complete occlusion of intracranial aneurysms treated by flow-diverter stents using machine learning.

BACKGROUND: Complete occlusion of an intracranial aneurysm (IA) after the deployment of a flow-diverter stent is currently unpredictable. The aim of t...

Hysteresis Modulation on Van der Waals-Based Ferroelectric Field-Effect Transistor by Interfacial Passivation Technique and Its Application in Optic Neural Networks.

2D semiconductor-based ferroelectric field effect transistors (FeFETs) have been considered as a promising artificial synaptic device for implementati...

Design and testing of a novel gastrointestinal microrobot.

In order to improve the reliability, safety and whole digestive applicability of the gastrointestinal microrobot (GMR), a novel inchworm-like GMR is p...

Artificial Intelligence to Identify Arthroplasty Implants From Radiographs of the Hip.

BACKGROUND: The surgical management of complications surrounding patients who have undergone hip arthroplasty necessitates accurate identification of ...

A Deep Learning-Based Approach for the Detection of Early Signs of Gingivitis in Orthodontic Patients Using Faster Region-Based Convolutional Neural Networks.

Computer-based technologies play a central role in the dentistry field, as they present many methods for diagnosing and detecting various diseases, su...

Automatic detection of COVID-19 from chest radiographs using deep learning.

INTRODUCTION: The breakdown of a deadly infectious disease caused by a newly discovered coronavirus (named SARS n-CoV2) back in December 2019 has show...

Replicating dynamic humerus motion using an industrial robot.

Transhumeral percutaneous osseointegrated prostheses provide upper-extremity amputees with increased range of motion, more natural movement patterns, ...

Use of Deep Learning to Analyze Social Media Discussions About the Human Papillomavirus Vaccine.

IMPORTANCE: Human papillomavirus (HPV) vaccine hesitancy or refusal is common among parents of adolescents. An understanding of public perceptions fro...

Machine learning model demonstrates stunting at birth and systemic inflammatory biomarkers as predictors of subsequent infant growth - a four-year prospective study.

BACKGROUND: Stunting affects up to one-third of the children in low-to-middle income countries (LMICs) and has been correlated with decline in cogniti...