1,720,957 research outputs found
A semi-Supervised Deep Learning Approach to Automate the Identification of Fetal Behavioral States in Fetal Heart Rate Tracings
No full textComputerized Cardiotocography (cCTG) facilitates a thorough and objective examination of the Fetal Heart Rate (FHR), providing valuable insights into the fetal condition and its well-being. A crucial aspect within this context pertains to the automatic identification of periods of fetal activity and quiescence, which are associated with different FHR patterns. The accurate discrimination of these patterns holds the potential to improve the interpretability and diagnostic capabilities of FHR quantitative analysis. Indeed, disruptions in the cycling between active and quiet periods are associated with the development of pathological conditions. This study introduces a deep learning based methodology for the identification of fetal behavioral heart rate patterns. Specifically, the implemented deep neural network (DNN) adopts a 1D encoder-decoder architecture, which is trained to recognize and automatically segment the FHR recordings into active and quiet periods. The proposed framework includes a semi-supervised training process, based on two steps: a) DNN pre-training based on pseudo-labels generated by a Hidden Markov Model (HMM), b) DNN fine-tuning integrating the annotations of an expert Ob-Gyn clinician. The trained DNN exhibits promising results: Balanced Accuracy of 88.37%, Macro F1-Score of 87.87% and Matthews Correlation Coefficient (MCC) of 75.80% on a distinct hold-out test set, encompassing 45 FHR traces annotated by an expert Ob-Gyn clinician
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
Hidden Markov Models and Deep Neural Networks: segmentation of the Fetal Heart Rate signal into behavioral patterns
Get PDFLAUREA MAGISTRALELa cardiotocografia è una tecnica di monitoraggio molto diffusa per la valutazione del benessere fetale che prevede la registrazione simultanea della frequenza cardiaca fetale e delle contrazioni uterine, possibilmente insieme ai movimenti fetali. Nelle fasi finali della gravidanza emergono quattro differenti stati comportamentali fetali: sonno quieto, sonno attivo, veglia quieta e veglia attiva. La loro precisa determinazione richiede tuttavia la misurazione simultanea e oggettiva di pattern di frequenza cardiaca, movimenti del corpo e movimenti oculari. Nel contesto della cardiotocografia è più comune distinguere solo tra stati di attività e di quiete, e il passaggio ciclico tra questi viene considerato un segno distintivo di benessere fetale. Lo scopo di questa tesi è lo sviluppo di algoritmi per la segmentazione automatica della traccia della frequenza cardiaca fetale in pattern di attività e di quiete, indicativi dello stato comportamentale fetale. Un totale di 115 tracce annotate, fornite da un ginecologo esperto, sono state usate come riferimento per le varie fasi del progetto. Inizialmente sono stati utilizzati hidden Markov model (HMM) non supervisionati, a partire da diversi parametri calcolati su ciascuna traccia di frequenza cardiaca fetale usando finestre mobili. È stata posta particolare attenzione nell'indagare se l’inclusione dell'età gestazionale della gravidanza potesse portare ad un miglioramento della segmentazione del segnale. Tuttavia la pipeline sviluppata ha mostrato poco margine di miglioramento, il che ha portato a optare per approcci basati su tecniche di deep learning. La rete neurale è stata prima pre-allenata usando pseudo-label generate dall'HMM, sfruttando quindi l'ampio set di dati non annotati a disposizione. Il modello è stato poi ulteriormente rifinito usando una porzione delle annotazioni fornite dal clinico. Infine, la rete neurale è stata valutata su un dataset di test separato, calcolando il Macro F1-Score traccia per traccia e ottenendo un risultato mediano del 90,19%, significativamente superiore rispetto al precedente HMM.Cardiotocography is a widespread monitoring technique for the assessment of fetal well-being which involves the simultaneous measurement of the fetal heart rate and uterine contractions, possibly along with fetal movements. In the final stages of pregnancy four different fetal behavioral states emerge: quiet sleep, active sleep, quiet awake and active awake. Their precise determination necessitates however the simultaneous and objective measurement of heart rate patterns, body movements, and eye movements. In the context of cardiotocography, it is more common to distinguish only between active and quiet states, and the cycling between these is considered a hallmark of fetal well-being. The purpose of this thesis is the development of algorithms for the automatic segmentation of fetal heart rate traces into active and quiet patterns, indicative of the underlying fetal behavioral state. A total of 115 labeled traces provided by an expert gynecologist were used as reference data for the various steps of the project. First, unsupervised hidden Markov models (HMM) were employed, starting from several parameters which were computed using sliding windows on each fetal heart rate trace. A specific emphasis was given on investigating whether considering the gestational age of the pregnancy could improve the signal segmentation. However, the developed unsupervised pipeline showed little room for improvement, which led to a transition towards a deep learning approach. The developed neural network was first pre-trained on pseudo-labels generated by the HMM, leveraging the abundant unlabeled set at disposal. The model was then fine-tuned using a portion of the labeled set provided by the expert clinician. Finally, the proposed neural network was evaluated on a separate hold-out test set, obtaining a median Macro F1-Score of 90.19% in a trace-by-trace comparison, significantly outperforming the previously developed HMM
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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