1,720,987 research outputs found
Medical Data Processing and Analysis
No full textMedical data can be defined as obtaining information from patients (such as signals, images, sounds, chemical components and their concentration, body temperature, respiratory rate, blood pressure, and different treatment measurements) to quantify the patient’s status and disease stage. Computer-aided diagnostic (CAD) systems use classical image processing, computer vision, machine learning, and deep learning methods for image analysis. Using image classification or segmentation algorithms, they find a region of interest (ROI) pointing to a specific location within the given image or an outcome of interest in the form of a label pointing to a diagnosis or prognosis. Computer science, with the evolution of artificial intelligence and machine learning techniques, facilitates the modeling and interpretation of results—from carrying out measurements to experiments and observations. Employing technological tools for collection, processing, and analysis incorporates understanding the patient’s status and developing the treatment plan. Achieving highly accurate models requires a huge dataset. This issue can be solved by having enough knowledge around medical data processing and their analysis. This reprint shows state-of-the-art research in the field of medical data processing and analysis. The medical data are represented in signals, images, raw data, protein sequences, etc. Processing and analysis of any kind can indicate specific issues in the medical sector such as diagnosis, detection, prediction, and segmentation to enhance the visualization of the processed dat
Advances in Medical Image Processing, Segmentation and Classification
No full textMedical data typically include physiological signals, diagnostic images, and treatment histories, offering essential insights into patient conditions and outcomes. Computer-aided diagnosis (CAD) systems—used for detection, segmentation, and classification—are now key components of clinical workflows. These systems apply image processing techniques to ensure accurate analysis across CT, MRI, X-ray, and ultrasound scans. Artificial intelligence (AI), especially machine learning and deep learning, has further advanced CAD by enabling automated, accurate disease detection. Yet, the success of such models depends on large, annotated datasets and expertise in preprocessing, modeling, and validation. AI-driven CAD systems have shown strong potential in diverse clinical settings. Future work should prioritize multi-center data sharing, federated learning, few-shot learning, and explainable AI to enhance reliability and adaptability. Integrating AI with technologies like the Internet of Medical Things (IoMT) opens doors to real-time, scalable diagnostics. With continued innovation and rigorous validation, AI is set to become an essential part of clinical decision-making. This volume presents cutting-edge research and strategies to address current gaps, aiming to improve patient outcomes and advance global healthcare systems
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
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
Causes and alternative treatments of neurological conditions due to environmental toxins:An overview
No full textIt is fairly obvious that we live in a toxic world and our brains are poisoned continuously, and this constant low level of exposure over time is slowly damaging our neurons and brain cells. The worse news is that this harmful toxic environment is not going to stop anytime in the foreseeable future and environmental toxins are a leading cause of neurological illnesses. It is also well established that oxidative stress contributes to various diseases including diabetes, heart disease, inflammatory conditions, high blood pressure, and neurological diseases such as Alzheimer's and Parkinson's. It is therefore inevitable that exposure to such conditions including heavy metals, EMF radiation, bacteria and viruses will require a strong immune system to defeat such harmful toxins, and that almost 80 percent of the immune system is located in the gut. The main causes of neurological diseases are already known and the standard drug treatments (e.g., Aricept and Namenda for Alzheimer's) slow the progression of such terrible diseases, but they do not address the root cause of memory loss. Glutathione is known as body's master antioxidant being effective against oxidative stress and inflammation. Along with other natural antioxidants in the body, it works to defeat the harmful effects of free radicals which cause damage to cells and tissue leading to various health conditions. In this review, the main factors, including environmental toxins, causing neurological illnesses like Alzheimer's and Parkinson's, and natural ways of prevention and treatment protocols have been discussed. The proposed treatment protocol could be lifesaving and is supported by the extensively published literature. </p
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
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