1,720,974 research outputs found
Artificial Intelligence and Machine Learning Applications in Clinical Biomechanics: A Systematic Review
No full textBackground: Artificial Intelligence (AI) and Machine Learning (ML) are rapidly transforming biomechanical research, potentially addressing limitations of traditional laboratory-based motion capture and observational analysis methods that are often time-consuming, expensive, and confined to controlled environments.
Purpose: To systematically review and synthesize evidence on AI/ML applications in clinical biomechanical analysis, evaluating their accuracy, validation methodologies, and clinical translation potential across different biomechanical parameters from 2020-2025.
Methods: Following PRISMA guidelines, we systematically searched nine databases for articles published between January 2020 and April 2025. Included studies directly addressed AI/ML techniques for biomechanical parameter estimation in human subjects with clearly defined accuracy metrics. Data synthesis involved narrative analysis due to methodological heterogeneity. Quality assessment used the Downs and Black checklist.
Results: From 3,245 initial records, 186 studies met inclusion criteria. Deep Learning (DL) approaches dominated (77% of studies), with Long Short-Term Memory networks (32%) and Convolutional Neural Networks (28%) showing superior performance for temporal biomechanical data. Wearable sensor integration achieved clinically acceptable accuracy for key parameters: joint moments (relative Root Mean Square Error 4.0-19.5%), center of pressure trajectories (correlation coefficient >0.90), and joint angles (Root Mean Square Error 3-8°). Leave-subject-out validation consistently demonstrated 2-3 fold higher error rates compared to typical split validation, highlighting generalizability challenges across populations.
Conclusion: AI/ML techniques demonstrate significant potential for clinical biomechanical analysis, particularly through deep learning architectures integrated with wearable sensors. However, critical methodological challenges persist including validation standardization, model interpretability, and population generalizability that must be addressed before widespread clinical implementation
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Chaos theory modeling improves olecranodiaphyseal angle prediction from proximal ulnar dorsal angulation in healthy elbows
No full textAbstract To evaluate the relationship between Proximal Ulnar Dorsal Angulation (PUDA) and Olecranodiaphyseal Angle (ODA) in healthy elbows using both linear regression and advanced chaos theory approaches, analyzing the effects of age, sex, and side parameters. In this cross-sectional study, 295 healthy elbows (178 male, 117 female; 130 right, 165 left) were evaluated with standard radiographs. PUDA, Varus Angle (VA), and ODA measurements were performed by two independent observers. Linear regression analysis and chaos theory-based nonlinear modeling were used to establish mathematical relationships between PUDA and ODA. Phase space reconstruction, fractal dimension analysis, Lyapunov exponent calculation, and strange attractor identification were performed to characterize the underlying dynamical system. Linear analysis revealed an inverse relationship between PUDA and ODA (regression coefficient β = −0.340, significance level p < 0.001). However, chaos theory analysis uncovered complex nonlinear dynamics with a fractal attractor structure (correlation dimension D2 = 2.34 ± 0.12, indicating non-integer dimensional geometry) and positive Lyapunov exponent (λ1 = 0.127 ± 0.043, confirming sensitive dependence on initial conditions characteristic of chaotic behavior). The chaos-based local linear model achieved superior prediction accuracy (R2 = 0.758, RMSE = 2.53) compared to linear regression (R2 = 0.210, RMSE = 4.63), representing a 3.6-fold improvement. Bifurcation analysis identified critical PUDA threshold values where system behavior changed dramatically. Males exhibited higher dimensional complexity (correlation dimension D2 = 2.51 ± 0.18) compared to females (D2 = 2.14 ± 0.21, significance level p = 0.032), indicating that male proximal ulnar geometry is governed by more complex dynamical interactions. The chaotic dynamics underlying PUDA-ODA relationships provide superior predictive capability compared to traditional linear models. This chaos theory-based approach offers clinicians dramatically improved accuracy for estimating normal ODA values in complex elbow injuries, with precise predictions (± 2°) improving from 34.2 to 67.8% of cases. The identification of strange attractors and bifurcation points reveals that small variations in PUDA measurements can lead to dramatically different ODA predictions, emphasizing the critical importance of measurement precision in surgical planning
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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