Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 15.262
Filtrar
1.
Huan Jing Ke Xue ; 43(1): 37-45, 2022 Jan 08.
Artigo em Chinês | MEDLINE | ID: mdl-34989488

RESUMO

This study explores the effect of different ozone metrics on the total mortality risk in China. Using the CNKI, Wanfang, VIP, Web of Science, and PubMed databases, the time series studies and case crossover studies from the establishment of each database to December 31, 2020 were retrieved, and 22 eligible studies were included in this analysis. A meta-analysis was performed for the ozone metrics of O3-M1h, O3-M8h, and O3-24h. The results indicated that the increase in the total mortality risk is more closely associated with O3-M1h (RR #, 1.0052; 95%CI, 1.0031-1.0073) and is more weakly associated with O3-24h (RR #, 1.0036; 95%CI, 1.0025-1.0048) and O3-M8h (RR #, 1.0031; 95%CI, 1.0022-1.0041). A subgroup analysis of the three metrics revealed that the total mortality risk of ozone is higher in the cold season, the elderly (≥ 65) are more vulnerable to ozone pollution, and the total mortality risk in the north is higher than that in the south.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Ozônio , Idoso , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Benchmarking , China/epidemiologia , Humanos , Ozônio/análise
2.
BMC Health Serv Res ; 22(1): 17, 2022 Jan 02.
Artigo em Inglês | MEDLINE | ID: mdl-34974842

RESUMO

BACKGROUND: There is increased demand for urgent and acute services during the winter months, placing pressure on acute medicine services caring for emergency medical admissions. Hospital services adopt measures aiming to compensate for the effects of this increased pressure. This study aimed to describe the measures adopted by acute medicine services to address service pressures during winter. METHODS: A survey of acute hospitals was conducted during the Society for Acute Medicine Benchmarking Audit, a national day-of-care audit, on 30th January 2020. Survey questions were derived from national guidance. Acute medicine services at 93 hospitals in the United Kingdom completed the survey, evaluating service measures implemented to mitigate increased demand, as well as markers of increased pressure on services. RESULTS: All acute internal medicine services had undertaken measures to prepare for increased demand, however there was marked variation in the combination of measures adopted. 81.7% of hospitals had expanded the number of medical inpatient beds available. 80.4% had added extra clinical staff. The specialty of the physicians assigned to provide care for extra inpatient beds varied. A quarter of units had reduced beds available for providing Same Day Emergency Care on the day of the survey. Patients had been waiting in corridors within the emergency medicine department in 56.3% of units. CONCLUSION: Winter pressure places considerable demand on acute services, and impacts the delivery of care. Although increased pressure on acute hospital services during winter is widely recognised, there is considerable variation in the approach to planning for these periods of increased demand.


Assuntos
Benchmarking , Auditoria Médica , Serviço Hospitalar de Emergência , Hospitalização , Hospitais , Humanos , Reino Unido
3.
Environ Pollut ; 295: 118690, 2022 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-34921939

RESUMO

Surface ozone (O3) is a threat to forests by decreasing photosynthesis and, consequently, influencing the strength of land carbon sink. However, due to the lack of continuous surface O3 measurements, observational-based assessments of O3 impacts on forests are largely missing at hemispheric to global scales. Currently, some metrics are used for regulatory purposes by governments or national agencies to protect forests against the negative impacts of ozone: in particular, both Europe and United States (US) makes use of two different exposure-based metrics, i.e. AOT40 and W126, respectively. However, because of some limitations in these metrics, a new standard is under consideration by the European Union (EU) to replace the current exposure metric. We analyse here the different air quality standards set or proposed for use in Europe and in the US to protect forests from O3 and to evaluate their spatial and temporal consistency while assessing their effectiveness in protecting northern-hemisphere forests. Then, we compare their results with the information obtained from a complex land surface model (ORCHIDEE). We find that present O3 uptake decreases gross primary production (GPP) in 37.7% of the NH forested area of northern hemisphere with a mean loss of 2.4% year-1. We show how the proposed US (W126) and the currently used European (AOT40) air quality standards substantially overestimate the extension of potential vulnerable regions, predicting that 46% and 61% of the Northern Hemisphere (NH) forested area are at risk of O3 pollution. Conversely, the new proposed European standard (POD1) identifies lower extension of vulnerability regions (39.6%).


Assuntos
Poluentes Atmosféricos , Ozônio , Poluentes Atmosféricos/análise , Benchmarking , Monitoramento Ambiental , Florestas , Ozônio/análise , Ozônio/toxicidade , Medição de Risco
4.
IEEE Trans Pattern Anal Mach Intell ; 44(1): 404-415, 2022 01.
Artigo em Inglês | MEDLINE | ID: mdl-32750792

RESUMO

Large-scale distributed training of deep neural networks results in models with worse generalization performance as a result of the increase in the effective mini-batch size. Previous approaches attempt to address this problem by varying the learning rate and batch size over epochs and layers, or ad hoc modifications of batch normalization. We propose scalable and practical natural gradient descent (SP-NGD), a principled approach for training models that allows them to attain similar generalization performance to models trained with first-order optimization methods, but with accelerated convergence. Furthermore, SP-NGD scales to large mini-batch sizes with a negligible computational overhead as compared to first-order methods. We evaluated SP-NGD on a benchmark task where highly optimized first-order methods are available as references: training a ResNet-50 model for image classification on ImageNet. We demonstrate convergence to a top-1 validation accuracy of 75.4 percent in 5.5 minutes using a mini-batch size of 32,768 with 1,024 GPUs, as well as an accuracy of 74.9 percent with an extremely large mini-batch size of 131,072 in 873 steps of SP-NGD.


Assuntos
Aprendizado Profundo , Algoritmos , Benchmarking , Redes Neurais de Computação
5.
IEEE Trans Pattern Anal Mach Intell ; 44(1): 416-427, 2022 01.
Artigo em Inglês | MEDLINE | ID: mdl-32750817

RESUMO

Learning the similarity between images constitutes the foundation for numerous vision tasks. The common paradigm is discriminative metric learning, which seeks an embedding that separates different training classes. However, the main challenge is to learn a metric that not only generalizes from training to novel, but related, test samples. It should also transfer to different object classes. So what complementary information is missed by the discriminative paradigm? Besides finding characteristics that separate between classes, we also need them to likely occur in novel categories, which is indicated if they are shared across training classes. This work investigates how to learn such characteristics without the need for extra annotations or training data. By formulating our approach as a novel triplet sampling strategy, it can be easily applied on top of recent ranking loss frameworks. Experiments show that, independent of the underlying network architecture and the specific ranking loss, our approach significantly improves performance in deep metric learning, leading to new the state-of-the-art results on various standard benchmark datasets.


Assuntos
Algoritmos , Aprendizado Profundo , Benchmarking
6.
IEEE Trans Pattern Anal Mach Intell ; 44(1): 13-31, 2022 01.
Artigo em Inglês | MEDLINE | ID: mdl-32750821

RESUMO

The rapid development of deep neural networks (DNNs) in recent years can be attributed to the various techniques that address gradient explosion and vanishing. In order to understand the principle behind these techniques and develop new methods, plenty of metrics have been proposed to identify networks that are free of gradient explosion and vanishing. However, due to the diversity of network components and complex serial-parallel hybrid connections in modern DNNs, the evaluation of existing metrics usually requires strong assumptions, complex statistical analysis, or has limited application fields, which constraints their spread in the community. In this paper, inspired by the Gradient Norm Equality and dynamical isometry, we first propose a novel metric called Block Dynamical Isometry, which measures the change of gradient norm in individual blocks. Because our Block Dynamical Isometry is norm-based, its evaluation needs weaker assumptions compared with the original dynamical isometry. To mitigate challenging derivation, we propose a highly modularized statistical framework based on free probability. Our framework includes several key theorems to handle complex serial-parallel hybrid connections and a library to cover the diversity of network components. Besides, several sufficient conditions for prerequisites are provided. Powered by our metric and framework, we analyze extensive initialization, normalization, and network structures. We find that our Block Dynamical Isometry is a universal philosophy behind them. Then, we improve some existing methods based on our analysis, including an activation function selection strategy for initialization techniques, a new configuration for weight normalization, a depth-aware way to derive coefficients in SeLU, and initialization/weight normalization in DenseNet. Moreover, we propose a novel normalization technique named second moment normalization, which has 30 percent fewer computation overhead than batch normalization without accuracy loss and has better performance under micro batch size. Last but not least, our conclusions and methods are evidenced by extensive experiments on multiple models over CIFAR-10 and ImageNet.


Assuntos
Algoritmos , Redes Neurais de Computação , Benchmarking
7.
Appl Ergon ; 98: 103582, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34600307

RESUMO

OBJECTIVES: To provide an overview of protocols assessing the effect of occupational exoskeletons on users and to formulate recommendations towards a literature-based assessment framework to benchmark the effect of occupational exoskeletons on the user. METHODS: PubMed (MEDLINE), Web of Science database and Scopus were searched (March 2, 2021). Studies were included if they investigated the effect of one or more occupational exoskeletons on the user. RESULTS: In total, 139 eligible studies were identified, encompassing 33, 25 and 18 unique back, shoulder and other exoskeletons, respectively. Device validation was most frequently conducted using controlled tasks while collecting muscle activity and biomechanical data. As the exoskeleton concept matures, tasks became more applied and the experimental design more representative. With that change towards realistic testing environments came a trade-off with experimental control, and user experience data became more valuable. DISCUSSION: This evidence mapping systematic review reveals that the assessment of occupational exoskeletons is a dynamic process, and provides literature-based assessment recommendations. The homogeneity and repeatability of future exoskeleton assessment experiments will increase following these recommendations. The current review recognises the value of variability in evaluation protocols in order to obtain an overall overview of the effect of exoskeletons on the users, but the presented framework strives to facilitate benchmarking the effect of occupational exoskeletons on the users across this variety of assessment protocols.


Assuntos
Benchmarking , Exoesqueleto Energizado , Humanos , Ombro
8.
Neural Netw ; 145: 1-9, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34710786

RESUMO

Multi-view clustering has become an active topic in artificial intelligence. Yet, similar investigation for graph-structured data clustering has been absent so far. To fill this gap, we present a Multi-View Graph embedding Clustering network (MVGC). Specifically, unlike traditional multi-view construction methods, which are only suitable to describe Euclidean structure data, we leverage Euler transform to augment the node attribute, as a new view descriptor, for non-Euclidean structure data. Meanwhile, we impose block diagonal representation constraint, which is measured by the ℓ1,2-norm, on self-expression coefficient matrix to well explore the cluster structure. By doing so, the learned view-consensus coefficient matrix well encodes the discriminative information. Moreover, we make use of the learned clustering labels to guide the learnings of node representation and coefficient matrix, where the latter is used in turn to conduct the subsequent clustering. In this way, clustering and representation learning are seamlessly connected, with the aim to achieve better clustering performance. Extensive experimental results indicate that MVGC is superior to 11 state-of-the-art methods on four benchmark datasets. In particular, MVGC achieves an Accuracy of 96.17% (53.31%) on the ACM (IMDB) dataset, which is an up to 2.85% (1.97%) clustering performance improvement compared with the strongest baseline.


Assuntos
Inteligência Artificial , Redes Neurais de Computação , Benchmarking , Análise por Conglomerados , Aprendizagem
9.
Neural Netw ; 145: 90-106, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34735894

RESUMO

We introduce Interpolation Consistency Training (ICT), a simple and computation efficient algorithm for training Deep Neural Networks in the semi-supervised learning paradigm. ICT encourages the prediction at an interpolation of unlabeled points to be consistent with the interpolation of the predictions at those points. In classification problems, ICT moves the decision boundary to low-density regions of the data distribution. Our experiments show that ICT achieves state-of-the-art performance when applied to standard neural network architectures on the CIFAR-10 and SVHN benchmark datasets. Our theoretical analysis shows that ICT corresponds to a certain type of data-adaptive regularization with unlabeled points which reduces overfitting to labeled points under high confidence values.


Assuntos
Redes Neurais de Computação , Aprendizado de Máquina Supervisionado , Algoritmos , Benchmarking
10.
Neural Netw ; 145: 144-154, 2022 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34749027

RESUMO

We study the efficacy and efficiency of deep generative networks for approximating probability distributions. We prove that neural networks can transform a low-dimensional source distribution to a distribution that is arbitrarily close to a high-dimensional target distribution, when the closeness is measured by Wasserstein distances and maximum mean discrepancy. Upper bounds of the approximation error are obtained in terms of the width and depth of neural network. Furthermore, it is shown that the approximation error in Wasserstein distance grows at most linearly on the ambient dimension and that the approximation order only depends on the intrinsic dimension of the target distribution. On the contrary, when f-divergences are used as metrics of distributions, the approximation property is different. We show that in order to approximate the target distribution in f-divergences, the dimension of the source distribution cannot be smaller than the intrinsic dimension of the target distribution.


Assuntos
Benchmarking , Redes Neurais de Computação , Probabilidade
11.
Talanta ; 238(Pt 2): 123046, 2022 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-34801903

RESUMO

Green analytical chemistry encourages reducing the use of toxic chemicals/reagents, using energy-efficient equipment, and generating minimal waste. The recent trends in analytical method development focus on the miniaturization of the sample preparation devices, the development of solventless or solvent-minimized extraction techniques, and the utilization of less toxic solvents. The twelve principles of GAC serve as a basic guideline for inducing greenness in the analytical procedures. Despite these guidelines, in many conditions, some undesired steps are unavoidable. Therefore, it is important to evaluate the greenness of analytical procedures to assess and, if possible, reduce their impact on the environment and workers. Several metrics have been developed for the evaluation of the greenness of analytical procedures. Analytical Eco-Scale, Green Analytical Procedure Index, and Analytical Greenness Metric are among some important tools for assessing the greenness of analytical procedures. All these metrics take different aspects of the analytical procedure into account to provide the green index of the procedure. This review covered these metrics, their principles, and examples of their application to selected analytical procedures. The advantages and limitations of these metrics with the perspective of common reader/user are presented. We believe that this paper will inspire many new perspectives and developments in this area.


Assuntos
Benchmarking , Química Verde , Humanos , Miniaturização , Solventes
12.
Med Educ Online ; 27(1): 2010299, 2022 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-34866545

RESUMO

The authors conduct a narrative review of the quantitative observation metrics and psychometric scales utilized in the visual arts and medical education literature in order to provide medical educators with a 'toolkit' of quantitative metrics with which to design and evaluate novel visual arts-based pedagogies. These efforts are intended to support the AAMC and National Academy of Sciences, Engineering, and Medicine's aims to formally evaluate and integrate arts and humanities curricula into traditional scientific educational programming. The scales reviewed examine a variety of domains including tolerance for ambiguity, bias, burnout, communication, empathy, grit, and mindfulness/reflection. Observation skill, given the heterogeneity of quantitative metrics, is reviewed separately.


Assuntos
Benchmarking , Educação Médica , Currículo , Ciências Humanas , Humanos , Psicometria
13.
Waste Manag ; 138: 274-284, 2022 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-34920243

RESUMO

Waste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by providing a critical analysis of over ten existing waste datasets and a brief but constructive review of the existing Deep Learning-based waste detection approaches. This article collects and summarizes previous studies and provides the results of authors' experiments on the presented datasets, all intended to create a first replicable baseline for litter detection. Moreover, new benchmark datasets detect-waste and classify-waste are proposed that are merged collections from the above-mentioned open-source datasets with unified annotations covering all possible waste categories: bio, glass, metal and plastic, non-recyclable, other, paper, and unknown. Finally, a two-stage detector for litter localization and classification is presented. EfficientDet-D2 is used to localize litter, and EfficientNet-B2 to classify the detected waste into seven categories. The classifier is trained in a semi-supervised fashion making the use of unlabeled images. The proposed approach achieves up to 70% of average precision in waste detection and around 75% of classification accuracy on the test dataset. The code and annotations used in the studies are publicly available online1.


Assuntos
Aprendizado Profundo , Benchmarking , Plásticos
14.
Sci Total Environ ; 804: 150178, 2022 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-34798733

RESUMO

Coral reefs are likely to be exposed to more intense cyclones under climate change. Cyclone impacts are spatially highly variable given complex hydrodynamics, and coral-specific sensitivity to wave impacts. Predicting reef vulnerability to cyclones is critical to management but requires high resolution environmental data that are difficult to obtain over broad spatial scales. Using 30m-resolution wave modelling, we tested cyclonic and non-cyclonic wave metrics as predictors of coral damage on 22 reefs after severe cyclone Ita impacted the northern Great Barrier Reef, Australia in 2014. Analyses of coral cover change accounting for the type of coral along a gradient of vulnerability to wave damage (e.g., massive, branching, Acroporids) excluded cyclone-generated surface wave metrics (derived from wave height) as important predictors. Increased bottom stress wave environment (near-bed wave orbital velocity) due to Ita (Ita-Ub) explained spatial patterns of 17% to 46% total coral cover loss only when the initial abundance of Acroporids was accounted for, and only when exceeding 35% cover. Greater coral losses occurred closer to the cyclone path irrespective of coral type. Massive and encrusting corals, however, had losses exacerbated in higher non-cyclonic bottom-wave energy environments (nc-Ub). The effect of community composition on structural vulnerability to wave damage was more important predicting damage that the magnitude of the cyclone-generated waves, especially when reefs are surveyed well beyond where damaging waves are expected to occur. Exposure to Ita-Ub was greater in typically high nc-Ub environments with relatively low cover of the most fragile morphologies explaining why these were the least affected overall. We reveal that the common surface-wave metrics of cyclone intensity may not always be able to predict spatial impacts and conclude that reef vulnerability assessments need to account for chronic wave patterns and differences in community composition in order to provide predictive tools for future conservation and restoration.


Assuntos
Antozoários , Tempestades Ciclônicas , Animais , Benchmarking , Mudança Climática , Recifes de Corais , Ecossistema
15.
Otolaryngol Clin North Am ; 55(1): 183-191, 2022 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-34823716

RESUMO

As practicing clinicians, most of us have not had formal education on many of the business fundamentals that allow us to run a thriving practice. This article serves as a primer for understanding revenue cycle management, practical steps for engaging in insurance contract negotiation, and considerations for benchmarking the financial, operational, and human resources of your clinic.


Assuntos
Seguro , Otolaringologia , Benchmarking , Humanos , Negociação , Estados Unidos
16.
Int J Cancer ; 150(1): 28-37, 2022 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-34449879

RESUMO

Despite improved survival rates, cancer remains one of the most common causes of childhood death. The International Cancer Benchmarking Partnership (ICBP) showed variation in cancer survival for adults. We aimed to assess and compare trends over time in cancer mortality between children, adolescents and young adults (AYAs) and adults in the six countries involved in the ICBP: United Kingdom, Denmark, Australia, Canada, Norway and Sweden. Trends in mortality between 2001 and 2015 in the six original ICBP countries were examined. Age standardised mortality rates (ASR per million) were calculated for all cancers, leukaemia, malignant and benign central nervous system (CNS) tumours, and non-CNS solid tumours. ASRs were reported for children (age 0-14 years), AYAs aged 15 to 39 years and adults aged 40 years and above. Average annual percentage change (AAPC) in mortality rates per country were estimated using Joinpoint regression. For all cancers combined, significant temporal reductions were observed in all countries and all age groups. However, the overall AAPC was greater for children (-2.9; 95% confidence interval = -4.0 to -1.7) compared to AYAs (-1.8; -2.1 to -1.5) and adults aged >40 years (-1.5; -1.6 to -1.4). This pattern was mirrored for leukaemia, CNS tumours and non-CNS solid tumours, with the difference being most pronounced for leukaemia: AAPC for children -4.6 (-6.1 to -3.1) vs AYAs -3.2 (-4.2 to -2.1) and over 40s -1.1 (-1.3 to -0.8). AAPCs varied between countries in children for all cancers except leukaemia, and in adults over 40 for all cancers combined, but not in subgroups. Improvements in cancer mortality rates in ICBP countries have been most marked among children aged 0 to 14 in comparison to 15 to 39 and over 40 year olds. This may reflect better care, including centralised service provision, treatment protocols and higher trial recruitment rates in children compared to older patients.


Assuntos
Benchmarking , Mortalidade/tendências , Neoplasias/epidemiologia , Neoplasias/mortalidade , Sistema de Registros/estatística & dados numéricos , Adolescente , Adulto , Austrália/epidemiologia , Canadá/epidemiologia , Criança , Pré-Escolar , Dinamarca/epidemiologia , Feminino , Seguimentos , Humanos , Incidência , Lactente , Recém-Nascido , Masculino , Noruega/epidemiologia , Prognóstico , Taxa de Sobrevida , Suécia/epidemiologia , Reino Unido/epidemiologia , Adulto Jovem
17.
J Mech Behav Biomed Mater ; 125: 104909, 2022 01.
Artigo em Inglês | MEDLINE | ID: mdl-34736025

RESUMO

Ventral hernia repair is a common surgical procedure in abdominal surgery in which surgical mesh has become an essential tool to improve outcomes. To avoid recurrences the mesh needs to mimic the mechanical behavior of the abdominal wall. In this scenario the mechanical properties at the interface between the mesh and its surrounding tissue is critical for the performance of the device and, therefore, the success after surgery. We aimed to characterize and compare the mechanical behavior of the patented prototype mesh Spider and four commercial meshes at the mesh-tissue interface. The prototype mesh was designed based on the hypothesis that the best performance for a large-sized defect in a ventral hernia is obtained when the mesh presents an isotropic behavior. In contrast, commercial meshes presented significant anisotropic behavior. Mechanical properties of the meshes were characterized through uniaxial tensile tests. Longitudinal and transverse axes were defined for each mesh, and samples were cut in each axis orientation. Samples underwent uniaxial tensile testing, from which the elastic modulus in each axis was determined. The degree of anisotropy was calculated as the ratio between the elastic modulus in each axis. An in silico model of the ventral hernia defect was designed to simulate the mesh-tissue interface behavior via finite element method. Meshes were modeled by an hyperelastic orthotropic constitutive model, which allowed isotropic symmetry as particular case for the prototype mesh. Abdominal wall was modeled using a Neo-Hookean model. Once the simulations were launched, mesh-tissue interface behavior was evaluated through the difference between Von Mises stress values on either size of the interface, both on the external and the internal face of the mesh and abdominal wall. Mechanical response was anisotropic for all commercial meshes and isotropic for the Spider prototype. Among commercial, Ultrapro® was highly anisotropic. Tests revealed Gore-Tex® to be the stiffest, followed by Repol Angimesh®, Spider and Ultrapro®; Duramesh™  was found to be the most compliant. Concerning mesh-tissue behavior, simulation results revealed the Spider prototype and Duramesh™  to be the best; Spider due to its uniformity and lower stress difference thanks to its nearly isotropic behavior, and Duramesh™  due to its compliant behavior. Our results suggest that the compromise between stiffness and anisotropy must be considered in order to improve the mechanical performance of the meshes, bearing in mind that for large-sized ventral defects, nearly isotropic mesh ensures better performance.


Assuntos
Parede Abdominal , Telas Cirúrgicas , Parede Abdominal/cirurgia , Benchmarking
18.
J Strength Cond Res ; 36(1): 277-283, 2022 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-34941613

RESUMO

ABSTRACT: Merrigan, JJ, Stone, JD, Wagle, JP, Hornsby, WG, Ramadan, J, Joseph, M, and Hagen, JA. Using random forest regression to determine influential force-time metrics for countermovement jump height: a technical report. J Strength Cond Res 36(1): 277-283, 2022-The purpose of this study was to indicate the most influential force-time metrics on countermovement jump (CMJ) height using multiple statistical procedures. Eighty-two National Collegiate Athletic Association Division I American football players performed 2 maximal-effort, no arm-swing, CMJs on force plates. The average absolute and relative (i.e., power/body mass) metrics were included as predictor variables, whereas jump height was the dependent variable within regression models (p < 0.05). Best subsets regression (8 metrics, R2 = 0.95) included less metrics compared with stepwise regression (18 metrics, R2 = 0.96), while explaining similar overall variance in jump height (p = 0.083). Random forest regression (RFR) models included 8 metrics, explained ∼93% of jump height variance, and were not significantly different than best subsets regression models (p > 0.05). Players achieved higher CMJs by attaining a deeper, faster, and more forceful countermovement with lower eccentric-to-concentric force ratios. An additional RFR was conducted on metrics scaled to body mass and revealed relative mean and peak concentric power to be the most influential. For exploratory purposes, additional RFR were run for each positional group and suggested that the most influential variables may differ across positions. Thus, developing power output capabilities and providing coaching to improve technique during the countermovement may maximize jump height capabilities. Scientists and practitioners may use best subsets or RFR analyses to help identify which force-time metrics are of interest to reduce the selectable number of multicollinear force-time metrics to monitor. These results may inform their training programs to maximize individual performance capabilities.


Assuntos
Desempenho Atlético , Futebol Americano , Tutoria , Benchmarking , Estatura , Humanos , Força Muscular
19.
IEEE Trans Image Process ; 31: 894-905, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-34951847

RESUMO

Accurate gland segmentation in histology tissue images is a critical but challenging task. Although deep models have demonstrated superior performance in medical image segmentation, they commonly require a large amount of annotated data, which are hard to obtain due to the extensive labor costs and expertise required. In this paper, we propose an intra- and inter-pair consistency-based semi-supervised (I2CS) model that can be trained on both labeled and unlabeled histology images for gland segmentation. Considering that each image contains glands and hence different images could potentially share consistent semantics in the feature space, we introduce a novel intra- and inter-pair consistency module to explore such consistency for learning with unlabeled data. It first characterizes the pixel-level relation between a pair of images in the feature space to create an attention map that highlights the regions with the same semantics but on different images. Then, it imposes a consistency constraint on the attention maps obtained from multiple image pairs, and thus filters low-confidence attention regions to generate refined attention maps that are then merged with original features to improve their representation ability. In addition, we also design an object-level loss to address the issues caused by touching glands. We evaluated our model against several recent gland segmentation methods and three typical semi-supervised methods on the GlaS and CRAG datasets. Our results not only demonstrate the effectiveness of the proposed due consistency module and Obj-Dice loss, but also indicate that the proposed I2CS model achieves state-of-the-art gland segmentation performance on both benchmarks.


Assuntos
Técnicas Histológicas , Semântica , Benchmarking , Processamento de Imagem Assistida por Computador
20.
JAMA Netw Open ; 4(12): e2137515, 2021 12 01.
Artigo em Inglês | MEDLINE | ID: mdl-34905006

RESUMO

Importance: The frequency of use of endovenous thermal ablation (EVTA) to treat chronic venous insufficiency has increased rapidly in the US. Wide variability in EVTA use among physicians has been documented, and standard EVTA rates were defined in the 2017 Medicare database. Objective: To assess whether providing individualized physician performance reports is associated with reduced variability in EVTA use and cost savings. Design, Setting, and Participants: This prospective quality improvement study used data from all US Medicare patients aged 18 years or older who underwent at least 1 EVTA between January 1, 2017, and December 31, 2017, and between January 1, 2019, and December 31, 2019. All US physicians who performed at least 11 EVTAs yearly for Medicare patients in 2017 and 2019 were included in the assessment. Intervention: A performance report comprising individual physician EVTA use per patient with peer-benchmarking data was distributed to all physicians in November 2018. Main Outcomes and Measures: The mean number of EVTAs performed per patient was calculated for each physician. Physicians who performed 3.4 or more EVTA procedures per patient per year were considered outliers. The change in the number of procedures from 2017 to 2019 was analyzed overall and by inlier and outlier status. An economic analysis was also performed to estimate the cost savings associated with the intervention. Results: A total of 188 976 patients (102 222 in 2017 and 86 754 in 2019) who had an EVTA performed by 1558 physicians were included in the analysis. The median patient age was 72.2 years (IQR, 67.9-77.8 years); 67.3% of patients were female, and 84.9% were White. Among all physicians, the mean (SD) number of EVTAs per patient decreased from 2017 to 2019 (1.97 [0.85] vs 1.89 [0.77]; P < .001). There was a modest decrease in the mean number of EVTAs per patient among inlier physicians (1.83 [0.57] vs 1.78 [0.55]; P < .001) and a more substantial decrease among outlier physicians (4.40 [1.01] vs 3.67 [1.41] ; P < .001). Outliers in 2017 consisted of 90 physicians, of whom 71 (78.9%) reduced their EVTA use after the intervention. The number of EVTAs per patient decreased by a mean (SD) of 0.09 (0.46) procedures overall (median, 0.10 procedures [IQR, -0.10 to 0.30 procedures]; P < .001). The estimated cost savings associated with the decrease was $6.3 million in 2019. Conclusions and Relevance: In this quality improvement study, substantial variability in the number of EVTAs performed per patient was observed across the US. When physicians were provided with a 1-time peer-benchmarked performance report card, the timing of the intervention was associated with a significant decrease in the number of EVTAs performed per patient, particularly among outlier physicians. This quality improvement initiative was associated with reduced variability in EVTA use in the US and a substantial savings for Medicare.


Assuntos
Benchmarking/organização & administração , Ablação por Cateter/normas , Melhoria de Qualidade , Insuficiência Venosa/terapia , Adulto , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Prospectivos , Fatores de Tempo , Varizes/cirurgia
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...