1,721,051 research outputs found
Use of eye drops obtained from homologous blood source in the time of COVID-19: is there cause for ophthalmological concern?
No full textHow Artificial Intelligence Is Impacting on the STEM Education of Students with Disabilities: A Five Years Review
Full text linkArtificial intelligence promises to revolutionize our life, bringing significant advances in any fields: health, education, work and leisure time. This paper analyzes the last 5-year literature concerning the use of AI for supporting people with disabilities in education. The aim is to investigate the current state of art of accessible applications in the STEM (Science, Technology, Engineering, Mathematics) field and understand if contents and tools are accessible for all, regardless of personal need and abilities. Personalization and adaptation emerge as fundamental factors when designing for people with disabilities. Privacy and ethics aspects often neglected are very relevant. The analysis suggests that the STEM field still suffers from accessibility gaps, and current tools need to evolve and be increased to be exploited by different disabilities and ensure the same opportunities for every student, engaging, motivating, and empowering them.
A systematic review of chatbots in inclusive healthcare: insights from the last 5 years
Full text linkHealthcare is one of the most important sectors of our society, and during the COVID-19 pandemic a new challenge emerged—how to support people safely and effectively at home regarding their health-related problems. In this regard chatbots or conversational agents (CAs) play an increasingly important role, and are spreading rapidly. They can enhance not only user interaction by delivering quick feedback or responses, but also hospital management, thanks to several of their features. Considerable research is focused on making CAs more reliable, accurate, and robust. However, a critical aspect of chatbots is how to make them inclusive, in order to effectively support the interaction of users unfamiliar with technology, such as the elderly and people with disabilities. In this study, we investigate the current use of chatbots in healthcare, exploring their evolution over time and their inclusivity. The study was carried out on four digital libraries (ScienceDirect, IEEE Xplore, ACM Digital Library, and Google Scholar) on research articles published in the last 5 years, with a total of 21 articles describing chatbots implemented and actually used in the eHealth clinical area. The results showed a notable improvement in the use of chatbots in the last few years but also highlight some design issues, including poor attention to inclusion. Based on the findings, we recommend a different kind of approach for implementing chatbots with an inclusive accessibility-by-design approach
A Preliminary Evaluation of Generative AI Tools for Blind Users: Usability and Screen Reader Interaction
Full text linkThe increasing use of Generative Artificial Intelligence (GAI) tools such as ChatGPT, Copilot, Perplexity and Gemini opens up new possible scenarios for supporting work and everyday activities. For people who are blind, the usability of such tools through screen readers is crucial to ensure their use of such AI-based technologies. In this study, we explore the accessibility and usability of the interfaces of four popular AI-based tools via screen readers through a combination of semi-automated evaluations and inspections conducted by both sighted and blind accessibility experts and screen readers with more than 20 years of experience. Navigation, labeling of control elements, feedback mechanisms, and prompt handling were considered in the study. The results point to usability difficulties in all tools, particularly in navigation structure, clarity of feedback and interactive elements. Although this work empirically explores the accessibility of AI-based tools it brings out the first critical issues that deserve further investigation. However, they are based on a small group of experts and thus should be considered preliminary and useful for future studies
Generative AI as a New Assistive Technology for Web Interaction
No full textFor users who are unfamiliar with technology or rely on assistive tools such as screen readers, interacting with a web page can be challenging. Ensuring a seamless experience requires a well-designed user interface (UI) that prioritizes accessibility and usability. However, achieving this target demands specialized expertise from developers and can involve significant effort. In this context, Generative Artificial Intelligence (GAI) has become a valuable aid for improving access to information and facilitating interaction with web interfaces. To effectively enhance user interaction---such as accessing services or specific functionalities---AI-driven tools must first be capable of understanding the structure and content of a web page. This study investigates if GAIs can be exploited to assist the user when navigating through a website, describing the site contents, explaining the interface structure and interactive elements, and suggesting actions or procedures to follow to perform a certain task or accomplish a specific goal. This kind of assistive technology can benefit not only visually impaired people but also persons with cognitive impairment and, more generally, people that are not ``skilled'' with modern web applications, like seniors. Specifically, thirteen popular websites were analyzed by asking Copilot one hundred questions. Results suggest that GAIs have the potential to assist people in web tasks. However, limitations have still been detected, with 20{\%} of completely erroneous answers received from the navigation and interaction questions and 15{\%} for those related to structure, mainly detected in pages having scarce accessibility and sites having a complex HTML structure, respectively
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Targeting growth factor supply in keratopathy treatment: Comparison between maternal peripheral blood and cord blood as sources for the preparation of topical eye drops
No full textBackground. Epitheliotrophic growth factors (GF) can be supplied topically to patients with severe keratopathy through a variety of blood-derived products. We compared GF content in adult peripheral blood serum (PB-S) and cord blood serum (CB-S) as potential sources of GF. To limit inter-individual variability the assessment was performed in maternal-child pairs at the time of delivery. Material and methods. The amounts of epidermal GF (EGF), insulin-like GF (IGF), transforming GF-beta (TGF-β), vascular endothelial GF (VEGF) in CB units collected from the umbilical vein and PB from mothers (each group n=30) were estimated by enzyme-linked immunosorbent assays. Obstetric characteristics and haematological data were recorded from the archives of the Emilia Romagna Cord Blood Bank. Statistical evaluations were performed by Wilcoxon's test and correlations between variables were determined using Spearman's (ρ) coefficient; p-values <0.05 were considered statistically significant. Results. EGF, TGF-β and VEGF levels were significantly higher in CB-S than in PB-S (median 1,254.4 vs 646.0 pg/mL, 51.3 vs 38.4 μg/mL and 686.8 vs 30 pg/mL, respectively; all p<0.0001) whereas IGF content was significantly higher in PB-S than in CB-S (159.9 vs 53.5 pg/mL, respectively; p<0.0001). In CB-S, the CD34+ cell concentration appeared to be related to EGF, IGF and TGF-β levels whereas white blood cell count appeared to be related to EGF and TGF-β levels. VEGF levels showed no relation to the haematological parameters considered. Platelet counts were not related to GF level in either CB or PB. Discussion. The GF content in the two blood sources was different, with CB containing larger amounts. Each GF selectively regulates cellular processes involved in corneal healing, so the use of PB or CB should be targeted to supply specific GF on the basis of the type and severity of the keratopathy
Machine learning techniques in breast cancer preventive diagnosis: a review
Full text linkBreast cancer (BC) is known as the most prevalent form of cancer among women. Recent research has demonstrated the potential of Machine Learning (ML) techniques in predicting the five-year BC risk using personal health data. Support Vector Machine (SVM), Random Forest, K-NN (K-Nearest Neighbour), Naive Bayes, Neural Network, Decision Tree (DT), Logistic Regression (LR), Discriminant Analysis, and their variants are commonly employed in ML for BC analysis. This study investigates the factors influencing the performance of ML techniques in the domain of BC prevention, with a focus on dataset size and feature selection. The study's goal is to examine the effect of dataset cardinality, feature selection, and model selection on analytical performance in terms of Accuracy and Area Under the Curve (AUC). To this aim, 3917 papers were automatically selected from Scopus and PubMed, considering all publications from the previous 5 years, and, after inclusion and exclusion criteria, 54 articles were selected for the analysis. Our findings highlight how a good cardinality of the dataset and effective feature selection have a higher impact on the model's performance than the selected model, as corroborated by one of the studies, which gets extremely good results with all of the models employed
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