1,141 research outputs found
Weighing benefits and risks in aspects of security, privacy and adoption of technology in a value-based healthcare system
Technology can potentially enable the implementation of a value-based healthcare system, where the impact of quality of care is offered at optimised cost for maximised patient benefit. Technology can deliver value by aiding in data collection to evaluate outcomes and measure costs on a patient and population level. Healthcare organisations, however, face several challenges and risks that result almost exclusively from the use of these technologies
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Automated Measurement of Spatially Resolved Hair-Hair Single Fiber Adhesion.
The adhesion force between individual human hair fibers in a crosshair geometry was measured by observing their natural bending and adhesive jumps out of contact, using optical video microscopy. The hair fibers' natural elastic responses, calibrated by measuring their natural resonant frequencies, were used to measure the forces. Using a custom-designed, automated apparatus to measure thousands of individual hair-hair contacts along millimeter length scales of hair, it was found that a broad, yet characteristic, spatially variant distribution in adhesion force is measured on the 1 to 1000 nN scale for both clean and conditioner-treated hair fibers. Comparison between the measured adhesion forces and adhesion forces modeled from the hairs' surface topography (measured using confocal laser profilometry) shows they have a good order-of-magnitude agreement and have similar breadth and shape. The agreement between the measurements and the model suggests, perhaps unsurprisingly, that hair-hair adhesion is governed, to a first approximation, by the unique surface structure of the hairs' cuticles and, therefore, the large distribution in local mean curvature at the various individual contact points along the hairs' lengths. We posit that haircare products could best control the surface properties (or at least the adhesive properties) between hairs by directly modifying the hair surface microstructure
Resonance Effects in the Nonadiabatic Nonlinear Quantum Dimer
The quantum nonlinear dimer consisting of an electron shuttling between the
two sites and in weak interaction with vibrations, is studied numerically under
the application of a DC electric field. A field-induced resonance phenomenon
between the vibrations and the electronic oscillations is found to influence
the electronic transport greatly. For initially delocalization of the electron,
the resonance has the effect of a dramatic increase in the transport. Nonlinear
frequency mixing is identified as the main mechanism that influences transport.
A characterization of the frequency spectrum is also presented.Comment: 7 pages, 6 figure
A scoping review of digital twins in the context of the Covid-19 pandemic
Background: Digital Twins (DTs), virtual copies of physical entities, are a promising tool to help manage and predict outbreaks of Covid-19. By providing a detailed model of each patient, DTs can be used to determine what method of care will be most effective for that individual. The improvement in patient experience and care delivery will help to reduce demand on healthcare services and to improve hospital management. Objectives:: The aim of this study is to address 2 research questions: (1) How effective are DTs in predicting and managing infectious diseases such as Covid-19? and (2) What are the prospects and challenges associated with the use of DTs in healthcare? Methods:: The review was structured according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) framework. Titles and abstracts of references in PubMed, IEEE Xplore, Scopus, ScienceDirect and Google Scholar were searched using selected keywords (relating to digital twins, healthcare and Covid-19). The papers were screened in accordance with the inclusion and exclusion criteria so that all papers published in English relating to the use of digital twins in healthcare were included. A narrative synthesis was used to analyse the included papers. Results:: Eighteen papers met the inclusion criteria and were included in the review. None of the included papers examined the use of DTs in the context of Covid-19, or infectious disease outbreaks in general. Academic research about the applications, opportunities and challenges of DT technology in healthcare in general was found to be in early stages. Conclusions:: The review identifies a need for further research into the use of DTs in healthcare, particularly in the context of infectious disease outbreaks. Based on frameworks identified during the review, this paper presents a preliminary conceptual framework for the use of DTs for hospital management during the Covid-19 outbreak to address this research gap
Safety and acceptability of a natural-language AI assistant to deliver clinical follow-up to cataract surgery patients: Proposal for a pragmatic evaluation
Background: Due to an ageing population, the demand for many services is exceeding the capacity of the clinical workforce. As a result, staff are facing a crisis of burnout from being pressured to deliver high-volume workloads, driving increasing costs for providers. Artificial intelligence, in the form of conversational agents, presents a possible opportunity to enable efficiencies in the delivery of care. Aims and Objectives: This study aims to evaluate the effectiveness, usability, and acceptability of Dora - an AI-enabled autonomous telemedicine call - for detection of post-operative cataract surgery patients who require further assessment. The study’s objectives are to: 1) establish Dora’s efficacy in comparison to an expert clinician, 2) determine baseline sensitivity and specificity for detection of true complications, 3) evaluate patient acceptability, 4) collect evidence for cost-effectiveness, and 5) capture data to support further development and evaluation. Methods: Based on implementation science, the interdisciplinary study will be a mixed-methods phase one pilot establishing inter-observer reliability of the system, usability, and acceptability. This will be done using using the following scales and frameworks: the system usability scale; assessment of Health Information Technology Interventions in Evidence-Based Medicine Evaluation Framework; the telehealth usability questionnaire (TUQ); the Non-Adoption, Abandonment and Challenges to the Scale-up, Spread and Suitability (NASSS) framework. Results: The results will be included in the final evaluation paper, which we aim to publish in 2022. The study will last eighteen months: seven months of evaluation and intervention refinement, nine months of implementation and follow-up, and two months of post-evaluation analysis and write-up. Conclusions: The project’s key contributions will be evidence on artificial intelligence voice conversational agent effectiveness, and associated usability and acceptability
The effectiveness of artificial intelligence conversational agents in healthcare: a systematic review
Background: High demand on healthcare services and the growing capability of artificial intelligence has led to the development of conversational agents designed to support a variety of health-related activities - including behaviour change, treatment support, health monitoring, training, triage, and screening support. Automation of these tasks could free clinicians to focus on more complex work and increase accessibility to healthcare services for the general public. An overarching assessment of the acceptability, usability, and effectiveness of these agents in healthcare is needed to collate the evidence so that future development can target areas for improvement and potential for sustainable adoption. Objective: This systematic review aimed to assess the effectiveness and usability of conversational agents in healthcare and identify the elements that users like and dislike, to inform future research and development of these agents. Methods: PubMed, Medline (Ovid), EMBASE, CINAHL, Web of Science, and ACM Digital Library were systematically searched for articles published since 2008 that evaluated unconstrained natural language processing conversational agents used in healthcare. Endnote (version X9; Clarivate Analytics) reference management software was used for initial screening, then full-text screening was conducted by one reviewer. Data was extracted and risk of bias was assessed by one reviewer and validated by another. Results: A total of 31 studies were selected and included a variety of conversational agents - 14 chatbots (two of which were voice chatbots), 6 embodied conversational agents, 3 each of interactive voice response calls, virtual patients, and speech recognition screening systems, as well as one contextual question answering agent and one voice recognition triage system. Overall, the evidence reported was mostly positive or mixed. Usability and satisfaction performed well (27/30 and 26/31) and positive or mixed effectiveness was found in three quarters of the studies (23/30), but there were several limitations of the agents highlighted in specific qualitative feedback. Conclusions: The studies generally reported positive or mixed evidence for the effectiveness, usability, and satisfactoriness of the conversational agents investigated, but qualitative user perceptions were more mixed. The quality of many of the studies was limited, and improved study design and reporting is necessary to more accurately evaluate the usefulness of the agents in healthcare and identify key areas for improvement. Further research should also analyse the cost-effectiveness, privacy, and security of the agents
Amine functionalization of cholecyst-derived extracellular matrix with generation 1 PAMAM dendrimer
This document is the unedited author's version of a Submitted Work that was subsequently accepted for publication in Biomacromolecules, copyright © American Chemical Society after peer review. To access the final edited and published work, see http://pubs.acs.org/doi/pdf/10.1021/bm701055k.A method to functionalize cholecyst-derived extracellular matrix (CEM) with free amine groups was established in an attempt to improve its potential for tethering of bioactive molecules. CEM was incorporated with Generation-1 polyamidoamine (G1 PAMAM) dendrimer by using N-(3-dimethylaminopropyl)-N′-ethylcarbodiimide and N-hydroxysuccinimide cross-linking system. The nature of incorporation of PAMAM dendrimer was evaluated using shrink temperature measurements, Fourier transform infrared (FTIR) assessment, ninhydrin assay, and swellability. The effects of PAMAM incorporation on mechanical and degradation properties of CEM were evaluated using a uniaxial mechanical test and collagenase degradation assay, respectively. Ninhydrin assay and FTIR assessment confirmed the presence of increasing free amine groups with increasing quantity of PAMAM in dendrimer-incorporated CEM (DENCEM) scaffolds. The amount of dendrimer used was found to be critical in controlling scaffold degradation, shrink temperature, and free amine content. Cell culture studies showed that fibroblasts seeded on DENCEM maintained their metabolic activity and ability to proliferate in vitro. In addition, fluorescence cell staining and scanning electron microscopy analysis of cell-seeded DENCEM showed preservation of normal fibroblast morphology and phenotype
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