Devices and Vaccines

Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks.

Magnetic resonance imaging (MRI) has been proposed as a complimentary method to measure bone quality and assess fracture risk. However, manual segmentation of MR images of bone is time-consuming, limiting the use of MRI measurements in the clinical practice. The purpose of this paper is to present an automatic proximal femur segmentation method that is based on deep convolutional neural networks (...

Improved model adaptation approach for recognition of reduced-frame-rate continuous speech.

In distributed speech recognition applications, the front-end device that stands for any handheld electronic device like smartphones and personal digital assistants (PDAs) captures the speech signal, extracts the speech features, and then sends the speech-feature vector sequence to the back-end server for decoding. Since the front-end mobile device has limited computation capacity, battery power a...

A Randomized Control Trial Of Anti-Inflammatory Regional Hypothermia On Urinary Continence During Robot-Assisted Radical Prostatectomy.

The present study seeks to present a single-blind, randomized control trial of a hypothermic anti-inflammatory device, the endorectal cooling balloon ...

DrugMetab: An Integrated Machine Learning and Lexicon Mapping Named Entity Recognition Method for Drug Metabolite.

Drug metabolites (DMs) are critical in pharmacology research areas, such as drug metabolism pathways and drug-drug interactions. However, there is no ...

MRI-based automated detection of implanted low dose rate (LDR) brachytherapy seeds using quantitative susceptibility mapping (QSM) and unsupervised machine learning (ML).

BACKGROUND AND PURPOSE: Permanent seed brachytherapy is an established treatment option for localized prostate cancer. Currently, post-implant dosimet...

Live-cell phenotypic-biomarker microfluidic assay for the risk stratification of cancer patients via machine learning.

The risk stratification of prostate cancer and breast cancer tumours from patients relies on histopathology, selective genomic testing, or on other me...

Memetic Search Optimization Along with Genetic Scale Recurrent Neural Network for Predictive Rate of Implant Treatment.

Implant treatment is one of the most important surgical processes in teeth which reduces the difficulties in teeth by providing the interface between ...

MoS Memristors Exhibiting Variable Switching Characteristics toward Biorealistic Synaptic Emulation.

Memristors based on 2D layered materials could provide biorealistic ionic interactions and potentially enable construction of energy-efficient artific...

Updated NACI recommendations for measles post-exposure prophylaxis.

BACKGROUND: Human immune globulin (Ig) products are currently recommended as post-exposure prophylaxis (PEP) for measles in certain susceptible groups...

Representing vaccine misinformation using ontologies.

BACKGROUND: In this paper, we discuss the design and development of a formal ontology to describe misinformation about vaccines. Vaccine misinformatio...

Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding Prediction.

Many chemicals that disrupt endocrine function have been linked to a variety of adverse biological outcomes. However, screening for endocrine disrupti...

Robotic selection for the rapid development of stable CHO cell lines for HIV vaccine production.

The production of envelope glycoproteins (Envs) for use as HIV vaccines is challenging. The yield of Envs expressed in stable Chinese Hamster Ovary (C...

PIP-EL: A New Ensemble Learning Method for Improved Proinflammatory Peptide Predictions.

Proinflammatory cytokines have the capacity to increase inflammatory reaction and play a central role in first line of defence against invading pathog...

An effective teeth recognition method using label tree with cascade network structure.

In this article, we apply the deep learning technique to medical field for the teeth detection and classification of dental periapical radiographs, wh...

Assessing Wrist Movement With Robotic Devices.

Robotic devices have been proposed to meet the rising need for high intensity, long duration, and goal-oriented therapy required to regain motor funct...

Using a deep learning network to recognise low back pain in static standing.

Low back pain (LBP) remains one of the most prevalent musculoskeletal disorders, while algorithms that able to recognise LBP patients from healthy pop...

Ischemic stroke lesion segmentation using stacked sparse autoencoder.

Automatic segmentation of ischemic stroke lesion volumes from multi-spectral Magnetic Resonance Imaging (MRI) sequences plays a vital role in quantify...

Thread/paper- and paper-based microfluidic devices for glucose assays employing artificial neural networks.

This paper describes the fabrication of and data collection from two microfluidic devices: a microfluidic thread/paper based analytical device (μTPAD)...

Hybrid Semantic Analysis for Mapping Adverse Drug Reaction Mentions in Tweets to Medical Terminology.

Social networks, such as Twitter, have become important sources for active monitoring of user-reported adverse drug reactions (ADRs). Automatic extrac...

Drug repositioning for prostate cancer: using a data-driven approach to gain new insights.

UNLABELLED: Prostate cancer (PC) is the most common cancer and the third leading cause of cancer death in men worldwide. Despite its high incidence an...