1,720,953 research outputs found

    Explainable AI for colorectal cancer detection using vision transformers

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    LAUREA MAGISTRALEIl cancro del colon-retto è una delle neoplasie più comuni e letali a livello globale, carat- terizzato dalla crescita incontrollata di cellule nel colon o nel retto. La diagnosi precoce tramite imaging medico è fondamentale per migliorare la prognosi dei pazienti, poiché consente trattamenti tempestivi e riduce i tassi di mortalità. I recenti progressi nellambito del deep learning hanno mostrato un notevole potenziale nellanalisi di immagini mediche; tuttavia, la mancanza di spiegabilità in molti modelli rappresenta una sfida per ladozione clinica. Questo lavoro esplora l’applicazione dei modelli Vision Transformer (ViT) per la rilevazione del cancro del colon-retto, con particolare attenzione alla spiegabilità del modello. Lenfasi è posta sullutilizzo di tecniche di explainability che evidenziano le regioni salienti delle immagini che contribuiscono alle predizioni del modello, offrendo così trasparenza e favorendo la fiducia tra i professionisti medici. Il modello ViT-base-224 è stato addestrato su due dataset di riferimento, Kvasir e Colorectal Histology-MNIST, raggiungendo unaccuratezza rispettivamente del 92.49 Per valutare la spiegabilità del modello, sono stati impiegati due metodi: Attention Rollout e Grad-CAM. La qualità delle spiegazioni è stata misurata tramite le metriche average drop e faithfulness. I risultati mostrano che Attention Rollout genera mappe di salienza più fedeli e che preservano meglio la confidenza del modello nel dataset Kvasir (average drop = 0.29, faithfulness = 0.42) rispetto a Histology-MNIST (average drop = 0.50, faith- fulness = 0.28), indicando una migliore localizzazione visiva delle caratteristiche rilevanti nelle immagini endoscopiche. Il confronto con Grad-CAM ha confermato la superiore coerenza e interpretabilità delle spiegazioni basate sullattenzione nei modelli transformer. Nel complesso, i risultati dimostrano lefficacia dei Vision Transformer sia in termini di performance di classificazione che di spiegabilità nel contesto dellimaging medico, sottolin- eando inoltre linfluenza delle caratteristiche del dataset e delle modalità di addestramento sulla qualità dellinterpretabilità.Colorectal cancer is one of the most common and lethal malignancies worldwide, char- acterized by the uncontrolled growth of cells in the colon or rectum. Early detection through medical imaging is critical for improving patient outcomes, as timely diagnosis enables effective treatment and reduces mortality rates. Recent advances in deep learning have demonstrated significant potential in medical image analysis, yet the lack of explain- ability in many models poses challenges for clinical adoption. This work explores the application of Vision Transformer (ViT) models for colorectal cancer detection and the assessment of model explainability. This work places a strong emphasis on explainability by employing different explainability techniques. These methods highlight salient regions in the images that contribute to the models predictions, thereby providing transparency and fostering trust among medical practitioners. The Vit-base-224 model was trained on two benchmark datasets, Kvasir and Colorectal Histology-MNIST achieving accuracies of 92.49% and 97.18%, respectively. To assess model explainability, two explainability meth- ods were employed: Attention rollout and Grad-CAM. The quality of explanations was evaluated using average drop and faithfulness metrics. Results showed that attention roll- out generated more faithful and confidence-preserving saliency maps on the Kvasir dataset (average drop = 0.29, faithfulness = 0.42) compared to Histology-MNIST (average drop = 0.50, faithfulness = 0.28), indicating better visual localization of relevant features in endoscopy images. A comparison with Grad-CAM confirmed the superior alignment and interpretability of attention-based explanations for transformer architectures. Overall, the findings demonstrate the effectiveness of Vision Transformers in both classification performance and explainability for medical imaging, while also emphasizing the impact of dataset characteristics and model training paradigms on interpretability quality

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The 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

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    “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

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    We 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

    Dispelling the Myths Behind First-author Citation Counts

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    We 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

    Author Index

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    koamabayili/VECTRON-author-checklist: VECTRON author checklist

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    We 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 Under Sail The Imagination of Jack London, 1893-1902

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    In Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
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