Publications by authors named "Taddeo M"

Machine unlearning (MU) is often analyzed in terms of how it can facilitate the "right to be forgotten." In this commentary, we show that MU can support the OECD's five principles for trustworthy AI, which are influencing AI development and regulation worldwide. This makes it a promising tool to translate AI principles into practice.

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Background: Alzheimer's disease and related dementias (ADRD) are among the most feared age-related conditions. The aim of this study was to evaluate a brief psychological intervention to promote adaptive coping in older adults experiencing heightened fear of ADRD and investigate positive downstream effects on health-related secondary outcomes, including frequency of reported memory failures, psychosocial functioning, and quality of life.

Methods: Eighty-one older adults were recruited and randomized into REFRAME or active control intervention arms.

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Introduction: L-carnitine (LC) has been associated with inflammatory mediator reduction and with downregulating the angiotensin-converting enzyme-2 (ACE2) receptor, which is the target of SARS-CoV-2 attachment.

Methods: This pilot phase 2 randomized, double-blind placebo-controlled trial contained two cohorts. Cohort 1 comprised 101 individuals with negative RT-PCR SARS-CoV-2 test results who cohabitated with an individual diagnosed with SARS-CoV-2 infection.

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This work aimed at evaluating the potential of amphiphilic polyoxazolines bearing lipid chain called lipopolyoxazolines to reach efficient intracellular delivery. Four lipid chains: linear saturated, linear unsaturated and two branched one of various length were associated to poly(2-methyl-2-oxazoline) block. The evaluation of their physicochemical features and their impact on cell viability and internalization capacity indicated that the linear saturated gathered the highest cell internalization with a good cell viability.

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Introduction: Alzheimer's disease and related dementias (ADRD) are among the most feared conditions. However, research around ADRD-specific fear and avoidance behaviors is lacking. Here, we validated a novel measure of fear and avoidance specific to memory loss, the Fear and Avoidance of Memory Loss (FAM) scale, and examined associations between fear avoidance and psychosocial functioning in older adults.

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Intelligence agencies have identified artificial intelligence (AI) as a key technology for maintaining an edge over adversaries. As a result, efforts to develop, acquire, and employ AI capabilities for purposes of national security are growing. This article reviews the ethical challenges presented by the use of AI for augmented intelligence analysis.

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Background: A high rate of COVID-19 vaccination is critical to reduce morbidity and mortality related to infection and to control the COVID-19 pandemic. Understanding the factors that influence vaccine confidence can inform policies and programs aimed at vaccine promotion. We examined the impact of health literacy on COVID-19 vaccine confidence among a diverse sample of adults living in two major metropolitan areas.

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Today, open source intelligence (OSINT), i.e., information derived from publicly available sources, makes up between 80 and 90 percent of all intelligence activities carried out by Law Enforcement Agencies (LEAs) and intelligence services in the West.

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This paper considers a host of definitions and labels attached to the concept of smart cities to identify four dimensions that ground a review of ethical concerns emerging from the current debate. These are: (1) network infrastructure, with the corresponding concerns of control, surveillance, and data privacy and ownership; (2) post-political governance, embodied in the tensions between public and private decision-making and cities as post-political entities; (3) social inclusion, expressed in the aspects of citizen participation and inclusion, and inequality and discrimination; and (4) sustainability, with a specific focus on the environment as an element to protect but also as a strategic element for the future. Given the persisting disagreements around the definition of a smart city, the article identifies in these four dimensions a more stable reference framework within which ethical concerns can be clustered and discussed.

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Background: Atopic dermatitis is a pruritic chronic condition associated with significant sleep disturbance, inattention, and sometimes behavioral problems. Enhancing resiliency in children with atopic dermatitis may promote coping strategies to improve quality of life. Positive psychology is one strategy that can be used to strengthen resiliency.

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In this report we focus on the definition of autonomous weapons systems (AWS). We provide a comparative analysis of existing official definitions of AWS as provided by States and international organisations, like ICRC and NATO. The analysis highlights that the definitions draw focus on different aspects of AWS and hence lead to different approaches to address the ethical and legal problems of these weapons systems.

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Background: Most health literacy measures require in-person administration or rely upon self-report.

Objective: We sought to develop and test the feasibility of a brief, objective health literacy measure that could be deployed via text messaging or online survey.

Design: Participants were recruited from ongoing NIH studies to complete a phone interview and online survey to test candidate items.

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Article Synopsis
  • The study explores how nonurological factors like anxiety, depression, physical function, and sleep quality affect male lower urinary tract symptoms (LUTS).
  • Data was analyzed from 518 men to identify relationships between psychological and physical health measures and various urinary symptom domains over time.
  • Findings show that depression and anxiety correlate with urinary issues, but their presence does not predict improvement after treatment, highlighting a need for further research to clarify these connections.
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In this commentary, we focus on the ethical challenges of data sharing and its potential in supporting biomedical research. Taking human genomics (HG) and European governance for sharing genomic data as a case study, we consider how to balance competing rights and interests-balancing protection of the privacy of data subjects and data security, with scientific progress and the need to promote public health. This is of particular relevancy in light of the current pandemic, which stresses the urgent need for international collaborations to promote health for all.

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Determining biomarkers and better characterizing the biochemical progression of nonalcoholic fatty liver disease (NAFLD) remains a clinical challenge. A targeted H-NMR study of serum, combined with clinical variables, detected and localized biomarkers to stages of NAFLD in morbidly obese females. Pre-surgery serum samples from 100 middle-aged, morbidly obese female subjects, grouped on gold-standard liver wedge biopsies (non-NAFLD; steatosis; and fibrosis) were collected, extracted, and analyzed in aqueous (DO) buffer (H, 600 MHz).

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Over the past few years, there has been a proliferation of artificial intelligence (AI) strategies, released by governments around the world, that seek to maximise the benefits of AI and minimise potential harms. This article provides a comparative analysis of the European Union (EU) and the United States' (US) AI strategies and considers (i) the visions of a 'Good AI Society' that are forwarded in key policy documents and their opportunity costs, (ii) the extent to which the implementation of each vision is living up to stated aims and (iii) the consequences that these differing visions of a 'Good AI Society' have for transatlantic cooperation. The article concludes by comparing the ethical desirability of each vision and identifies areas where the EU, and especially the US, need to improve in order to achieve ethical outcomes and deepen cooperation.

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In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that AI offers in this domain: it can help improve and expand current understanding of climate change, and it can contribute to combatting the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with AI, and the contribution to climate change of the greenhouse gases emitted by training data and computation-intensive AI systems.

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Background: Dementia is the most feared disease associated with aging. Prolonged fears about memory loss and dementia can have harmful consequences even in the absence of cognitive decline. Fear of dementia is associated with poorer health outcomes and psychological well-being and increased memory failures in older adults.

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Important decisions that impact humans lives, livelihoods, and the natural environment are increasingly being automated. Delegating tasks to so-called automated decision-making systems (ADMS) can improve efficiency and enable new solutions. However, these benefits are coupled with ethical challenges.

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Clostridioides difficile (CD) is a major nosocomial pathogen and the leading cause of antibiotic-associated diarrhoea. In light of the strong association between antimicrobial use and CD infections (CDI), it may be hypothesised that areas at higher prevalence of antimicrobial resistance, like the region of Campania in southern Italy, could also have a higher rate of CDI. In this multicentre, region-based, prospective study, we analysed such issues, exploiting CDI incidence data collected from local hospitals.

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The fact that Internet companies may record our personal data and track our online behavior for commercial or political purpose has emphasized aspects related to online privacy. This has also led to the development of search engines that promise no tracking and privacy. Search engines also have a major role in spreading low-quality health information such as that of anti-vaccine websites.

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Article Synopsis
  • The article reviews literature on the ethics of AI in healthcare to summarize ongoing debates and identify research gaps, focusing on ethical risks that policymakers and developers must address.
  • Ethical issues identified include epistemic (related to evidence), normative (unfair outcomes), and traceability concerns, categorized at various levels like individual and societal.
  • The authors stress the importance of addressing these ethical considerations promptly to maintain public trust in AI's benefits for healthcare, warning against potential negative consequences if action is delayed.
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