A Survey and Classification of Visualisation in Multiscale Biomedical Applications

2012 ◽  
Author(s):  
N.J.B. Mcfarlane ◽  
X. Ma ◽  
G.J. Clapworthy ◽  
N. Bessis ◽  
D. Testi
Keyword(s):  
Biomedical Applications

scholarly journals Moving Towards a Finer Way of Light-Cured Resin-Based Restorative Dental Materials: Recent Advances in Photoinitiating Systems Based on Iodonium Salts

Materials ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4093
Author(s):  
Monika Topa ◽  
Joanna Ortyl
Keyword(s):  
Biomedical Applications ◽  
Dental Materials ◽  
Dental Composites ◽  
Iodonium Salts ◽  
Photoinduced Polymerization ◽  
Low Energy Consumption ◽  
Restorative Dental Materials ◽  
Phosphine Derivatives ◽  
Short Time

The photoinduced polymerization of monomers is currently an essential tool in various industries. The photopolymerization process plays an increasingly important role in biomedical applications. It is especially used in the production of dental composites. It also exhibits unique properties, such as a short time of polymerization of composites (up to a few seconds), low energy consumption, and spatial resolution (polymerization only in irradiated areas). This paper describes a short overview of the history and classification of different typical monomers and photoinitiating systems such as bimolecular photoinitiator system containing camphorquinone and aromatic amine, 1-phenyl-1,2-propanedione, phosphine derivatives, germanium derivatives, hexaarylbiimidazole derivatives, silane-based derivatives and thioxanthone derivatives used in the production of dental composites with their limitations and disadvantages. Moreover, this article represents the challenges faced when using the latest inventions in the field of dental materials, with a particular focus on photoinitiating systems based on iodonium salts. The beneficial properties of dental composites cured using initiation systems based on iodonium salts have been demonstrated.

scholarly journals RECENT ADVANCES IN HYDROGELS FOR BIOMEDICAL APPLICATIONS

2018 ◽  
Vol 11 (11) ◽  
pp. 62
Author(s):  
Surojeet Das ◽  
Vivek Kumar ◽  
Rini Tiwari ◽  
Leena Singh ◽  
Sachidanand Singh
Keyword(s):  
Biomedical Applications ◽  
Three Dimensional ◽  
Primary Objective ◽  
Cellular Interactions ◽  
Natural Polymers ◽  
Synthetic Materials ◽  
Physical And Chemical ◽  
Modern Era ◽  
Synthetic And Natural Polymers

Hydrogels are three-dimensional polymeric network, capable of entrapping substantial amounts of fluids. Hydrogels are formed due to physical or chemical cross-linking in different synthetic and natural polymers. Recently, hydrogels have been receiving much attention for biomedical applications due to their innate structure and compositional similarities to the extracellular matrix. Hydrogels fabricated from naturally derived materials provide an advantage for biomedical applications due to their innate cellular interactions and cellular-mediated biodegradation. Synthetic materials have the advantage of greater tunability when it comes to the properties of hydrogels. There has been considerable progress in recent years in addressing the clinical and pharmacological limitations of hydrogels for biomedical applications. The primary objective of this article is to review the classification of hydrogels based on their physical and chemical characteristics. It also reviews the technologies adopted for hydrogel fabrication and the different applications of hydrogels in the modern era.

scholarly journals Multi-task deep learning for cardiac rhythm detection in wearable devices

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Jessica Torres-Soto ◽  
Euan A. Ashley
Keyword(s):  
Atrial Fibrillation ◽  
Heart Rate ◽  
Deep Learning ◽  
Biomedical Applications ◽  
Large Scale ◽  
High Sensitivity ◽  
Wearable Devices ◽  
Replication Cohort ◽  
Data Problem

Abstract Wearable devices enable theoretically continuous, longitudinal monitoring of physiological measurements such as step count, energy expenditure, and heart rate. Although the classification of abnormal cardiac rhythms such as atrial fibrillation from wearable devices has great potential, commercial algorithms remain proprietary and tend to focus on heart rate variability derived from green spectrum LED sensors placed on the wrist, where noise remains an unsolved problem. Here we develop DeepBeat, a multitask deep learning method to jointly assess signal quality and arrhythmia event detection in wearable photoplethysmography devices for real-time detection of atrial fibrillation. The model is trained on approximately one million simulated unlabeled physiological signals and fine-tuned on a curated dataset of over 500 K labeled signals from over 100 individuals from 3 different wearable devices. We demonstrate that, in comparison with a single-task model, our architecture using unsupervised transfer learning through convolutional denoising autoencoders dramatically improves the performance of atrial fibrillation detection from a F1 score of 0.54 to 0.96. We also include in our evaluation a prospectively derived replication cohort of ambulatory participants where the algorithm performed with high sensitivity (0.98), specificity (0.99), and F1 score (0.93). We show that two-stage training can help address the unbalanced data problem common to biomedical applications, where large-scale well-annotated datasets are hard to generate due to the expense of manual annotation, data acquisition, and participant privacy.

scholarly journals Models and Analysis of Vocal Emissions for Biomedical Applications

2013 ◽  
Keyword(s):  
Clinical Diagnosis ◽  
Biomedical Engineering ◽  
Biomedical Applications ◽  
Scientific Papers ◽  
Mechanical Models ◽  
Diagnosis And Classification

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies.

scholarly journals Models and analysis of vocal emissions for biomedical applications: 5th International Workshop: December 13-15, 2007, Firenze, Italy

2007 ◽  
Keyword(s):  
Biomedical Engineering ◽  
Biomedical Applications ◽  
International Workshop ◽  
Biomedical Signal Processing ◽  
Biomedical Signal ◽  
Scientific Papers ◽  
Mechanical Models ◽  
Diagnosis And Classification ◽  
And Control

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies. The Workshop has the sponsorship of: Ente Cassa Risparmio di Firenze, COST Action 2103, Biomedical Signal Processing and Control Journal (Elsevier Eds.), IEEE Biomedical Engineering Soc. Special Issues of International Journals have been, and will be, published, collecting selected papers from the conference.

scholarly journals Models and Analysis of Vocal Emissions for Biomedical Applications

2009 ◽  
Keyword(s):  
Clinical Diagnosis ◽  
Biomedical Engineering ◽  
Biomedical Applications ◽  
Scientific Papers ◽  
Mechanical Models ◽  
Diagnosis And Classification

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies.

Nanoscale in silico classification of ligand functionalised surfaces for protein adsorption resistance

Nanoscale ◽  
2020 ◽  
Vol 12 (13) ◽  
pp. 7240-7255
Author(s):  
Matthew Penna ◽  
Irene Yarovsky
Keyword(s):  
Protein Adsorption ◽  
In Silico ◽  
Biomedical Applications ◽  
Specific Protein ◽  
Protein Resistance ◽  
Functional Surfaces

Non-specific protein adsorption represents a challenge for the design of efficient and safe nanoparticles for biomedical applications. An in silico method is presented to design ligands imparting protein resistance to functional surfaces.

scholarly journals Models and Analysis of Vocal Emissions for Biomedical Applications

2011 ◽  
Keyword(s):  
Clinical Diagnosis ◽  
Biomedical Engineering ◽  
Biomedical Applications ◽  
Scientific Papers ◽  
Mechanical Models ◽  
Diagnosis And Classification

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies.

scholarly journals Immobilized enzymes: a comprehensive review

2021 ◽  
Vol 45 (1) ◽  
Author(s):  
Mohammad Rafiq Khan
Keyword(s):  
Twentieth Century ◽  
Biomedical Applications ◽  
Immobilized Enzymes ◽  
Enzyme Engineering ◽  
Main Body ◽  
Comprehensive Review ◽  
History Of ◽  
Engineering Conference ◽  
Proposed Modification

Abstract Background This article is a comprehensive review of the events recorded in the history of enzymology from twentieth century to the recent work of author’s groups on different biochemical aspects of the immobilized enzymes. The review differs from those presented before on the basis that it is not limited to one or few aspects. It extends its spectrum to a large number of aspects from the definition to biomedical applications of immobilized enzymes. Main body The author and his associates have proposed modification of classification of immobilized enzymes by Enzyme Engineering Conference 1971. His groups have worked on cell bound proteases of medicinal seeds and have given them the name of “naturally immobilized enzymes”. Thus, the author proposes that the enzymes may be basically classified into “naturally immobilized enzymes” and “artificially immobilized enzymes”. The artificially immobilized enzymes may be further sub-classified as done in 1971. Conclusion The classification suggested above sounds logical and thus acceptable to the author and his associates. The author and his associates also suggest some applications on the basis of their results on naturally immobilized enzymes.

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