Search results for "Big data"
showing 10 items of 311 documents
Long-term disability trajectories in relapsing multiple sclerosis patients treated with early intensive or escalation treatment strategies
2021
Background and aims: No consensus exists on how aggressively to treat relapsing–remitting multiple sclerosis (RRMS) nor on the timing of the treatment. The objective of this study was to evaluate disability trajectories in RRMS patients treated with an early intensive treatment (EIT) or with a moderate-efficacy treatment followed by escalation to higher-efficacy disease modifying therapy (ESC). Methods: RRMS patients with ⩾5-year follow-up and ⩾3 visits after disease modifying therapy (DMT) start were selected from the Italian MS Registry. EIT group included patients who received as first DMT fingolimod, natalizumab, mitoxantrone, alemtuzumab, ocrelizumab, cladribine. ESC group patients rec…
Molecular modeling in cardiovascular pharmacology: Current state of the art and perspectives.
2021
Abstract Molecular modeling in pharmacology is a promising emerging tool for exploring drug interactions with cellular components. Recent advances in molecular simulations, big data analysis, and artificial intelligence (AI) have opened new opportunities for rationalizing drug interactions with their pharmacological targets. Despite the obvious utility and increasing impact of computational approaches, their development is not progressing at the same speed in different fields of pharmacology. Here, we review current in silico techniques used in cardiovascular diseases (CVDs), cardiological drug discovery, and assessment of cardiotoxicity. In silico techniques are paving the way to a new era…
Could Cambridge Analytica Have Delivered Donald Trump’s 2016 Presidential Victory? An Anthropologist’s Look at Big Data and Political Campaigning
2021
Abstract I first provide some context about Cambridge Analytica’s (ca) activities, linking them to ca parent company, scl Group, which specialised in “public relations” campaigns around the world across multiple sectors (from politics to defence and development), with the explicit aim of behavioural change. I then analyse in more detail the claims made by mathematician and machine learning scholar David Sumpter, who dismisses the possibility that ca might have successfully deployed internet psychographics (e.g. online personality profiling) in the winning 2016 Trump presidential campaign in the US. I critique his arguments, pointing at the need to focus on the bigger picture and on the tota…
In varietate concordia?! Political parties’ digital political marketing in the 2019 European Parliament election campaign
2021
This article provides the first comprehensive analysis of how parties across 28 countries use digital political marketing on Facebook by drawing on the example of the 2019 European Parliament election. We introduce a theoretical model of political Facebook marketing and compare the paid media activity (sponsored posts, ads) of 186 parties to their owned media (posts) and earned media (user reactions, comments, shares). Our results concerning cross-country patterns indicate that differences in European parties’ paid media activity exist and only a few parties leverage sophisticated targeting strategies. Regarding temporal dynamics, we find that paid media is used to supplement owned media du…
Facebook’s Emotional Contagion Experiment as a Challenge to Research Ethics
2016
This article analyzes the ethical discussion focusing on the Facebook emotional contagion experiment published by the <em>Proceedings of the National Academy of Sciences</em> in 2014. The massive-scale experiment manipulated the News Feeds of a large amount of Facebook users and was successful in proving that emotional contagion happens also in online environments. However, the experiment caused ethical concerns within and outside academia mainly for two intertwined reasons, the first revolving around the idea of research as manipulation, and the second focusing on the problematic definition of informed consent. The article concurs with recent research that the era of social med…
Data granularity in mid-year life table construction
2020
[EN] Life tables have a substantial influence on both public pension systems and life insurance policies. National statistical agencies construct life tables from death rate estimates (𝑚���𝑥���), or death probabilities (𝑞���𝑥��� ), after applying various hypotheses to the aggregated figures of demographic events (deaths, migrations and births). The use of big data has become extensive across many disciplines, including population statistics. We take advantage of this fact to create new (more unrestricted) mortality estimators within the family of period-based estimators, in particular, when the exposed-to-risk population is computed through mid-year population estimates. We use actual d…
Big Data in Corporate Governance decision
2020
[EN] Progress in Big Data in recent years has grown exponentially, which has allowed the detection and processing of a large amount of data. Until recently, this fact was unattainable by the lack of mechanization of the corporate governance reports. This paper investigates the relationship between corporate governance decisions affect the indebtedness policies of 1,956 industrial companies listed in Europe and the USA over the period 2016–2018 (5,868 observations). To measure corporate governance decisions, we use detailed information on the expertise of audit committees, the proportion of independent directors, board structures and women's presence on corporate boards. Our findings, which …
Quality Improvement Based on Big Data Analysis
2016
Big data analysis has become an important trend in computer science. Quality improvement is a constant in current industry trends. In this paper, we present an idea of quality improvement based on big data analysis with the aid of linked data and ontologies in order to implement it in the case of automotive parts production. We consider defective automotive products and try to find the best refurbishment solution for them considering their characteristics. Moreover, we propose to develop a recommender system that is able to give recommendations in order to prevent or to alleviate defects and to provide insights for possible causes that led to these defective parts. This study intends to hel…
Esineiden internetin tiedonhallinnan ominaispiirteet
2017
Kandidaatintutkielma käsittelee esineiden internetin tiedonhallinnan ominaispiirteitä. Tutkielmassa määritellään esineiden internetin tiedonhallinnan erilaiset kokonaisuudet ja niihin liittyvät haasteet sekä arvioidaan esineiden internetin tiedonhallinnan mahdollistavia sovelluksia ja palveluita. Tiedonhallinnan eri ulottuvuuksia käsitellään tutkielmassa yhtenäisen viitekehyksen perusteella. Esineiden internetin tiedonhallinnan ominaispiirteitä arvioidaan tutkielmassa teknologisten ratkaisujen, havainnollistavien mallien sekä erilaisten kontekstien näkökulmista. Tutkimuksen tarkoituksena on muodostaa kokonaisvaltainen ja hyödyllinen käsitys esineiden internetin tiedonhallinnasta sekä siihen…
Semantic annotation and big data techniques for patent information processing
2017
This thesis analyzes approaches to generate semantic annotations on patent records, as well as on other structured data, by relying on the structure and semantic representation of documents. Information in patent records reflects how real-world technologies evolve, and the approximately 3 million annual new patent applications capture the global inventive frontier. The volume of this information is too big to be effectively analyzed purely with human effort, necessitating Big data approaches to analyze it with computer aided tools and techniques. Big data is a term that describes a massive volume of structured, semi structured and unstructured data that is so large to the point that it is d…