The influence factors of the patients’ usage intention of AI-based preliminary diagnosis tools : the case study of Ada

At present Artificial Intelligence (AI) is transforming the mechanisms and limitations of numerous industries. The healthcare sector is particularly affected with regard to the informative value of processing and analysing patient data through AI-based technologies. Public fund cuts and structural inefficiencies among other reasons, further aggregate the necessity of effectively employing the provided patient information. The majority of healthcare facilities, however, lack the resources or technical knowhow to realize the entire potential of Artificial Intelligence as a mean. As a consequence, emerging companies, that can be theoretically classified as the intermediate form of public and private establishments, have developed new concepts. The structural adaptability of so-called hybrid organizations facilitates the offering of specialized products and services adapted to the needs of patients. In this regard AI-based preliminary mobile diagnostic applications represent a promising opportunity to empower patients and positively influence the average health quality. The influence factors determining the adoption and usage intention of patients are yet unexplored. This dissertation therefore examined the patient’s perspective on AI-based preliminary diagnostic tools, in order to firstly expand the scope of present literature within this subject area and to identify the relevant key elements for the marketing and strategy measures of hybrid organizations operating in this field. The implications of this research include the recognition of the patients intended purpose of utilizing similar mobile applications, the consequently deriving strategic inferences, and a guidance for the marketing and communication efforts of comparable vendors.Atualmente, a inteligência artificial está a transformar os mecanismos e limitações de diversas indústrias. O sector da saúde é particularmente afetado pelo potencial informativo de processamento e análise de dados de pacientes através de tecnologias de inteligência artificial. Cortes orçamentais públicos e ineficiências a nível estrutural evidenciam a necessidade de, idealmente, empregar os dados de pacientes. Na sua maioria, as instalações de saúde carecem de recursos ou de conhecimento técnico para se inteirarem do potencial da inteligência artificial. Consequentemente, as empresas emergentes, que teoricamente podem ser classificadas como um formato intermédio entre estabelecimentos públicos e privados, definem um novo conceito. A adaptação estrutural das organizações híbridas facilita a oferta de produtos e serviços especializados às necessidades dos pacientes. Neste sentido, aplicações móveis de diagnóstico preliminar recorrendo a inteligência artificial, representam uma oportunidade promissora por conceder autonomia aos pacientes e influenciando positivamente a qualidade do sector da saúde. Os fatores determinantes da adoção e intenção de uso por parte dos pacientes está, ainda, por explorar. A presente dissertação examinou a perspetiva dos pacientes relativamente às ferramentas de diagnóstico preliminar com recurso à inteligência artificial, com o intuito inicial de expandir a literatura referente a esta temática e de identificar elementos fundamentais para as medidas de marketing e estratégia de organizações híbridas que operam neste meio. As implicações deste estudo incluem o reconhecimento de pacientes que tencionem recorrer a aplicações móveis semelhantes e suas subsequentes implicações estratégicas, assim como diretrizes a nível de marketing e estratégia para negócios equivalentes

Catching the Runaway Train Innovation Management in Russian Railways

This paper studies the innovation strategy of Russian Railways, the biggest transport company in the world. Russian Railways has chosen a strategy of international science, technology and innovation (STI) cooperation outside their own network. This strategy is a novel approach for Russian State-owned enterprises (SOE). Based on the analysis of innovation development program and interviews with managers, the paper studies the company’s experience with the chosen strategy. Thereby, the paper enhances the understanding of innovation processes in major public service companies which are crucial for the socio-economic processes inside and outside national boundaries

Advances in Lymphoma Molecular Diagnostics

Lymphomas encompass a diverse group of malignant lymphoid neoplasms. Over recent years much scientific effort has been undertaken to identify and understand molecular changes in lymphomas, resulting in a wide range of genetic alterations that have been reported across all types of lymphomas. As many of these changes are now incorporated into the World Health Organization’s defined criteria for the diagnostic evaluation of patients with lymphoid neoplasms, their accurate identification is crucial. Even if many alterations are not routinely evaluated in daily clinical practice, they may still have implications in risk stratification, treatment, prognosis or disease monitoring. Moreover, some alterations can be used for targeted treatment. Therefore, these advances in lymphoma molecular diagnostics in some cases have led to changes in treatment algorithms. Here, we give an overview of and discuss advances in molecular techniques in current clinical practice, as well as highlight some of them in a clinical context

StreamOnTheFly: a Peer-to-peer network for radio stations and podCasters

The StreamOnTheFly network demonstrates new ways of management and personalisation technologies for audio. The architecture is based on a decentralized network of software components using automatic metadata replication in a peer-to-peer manner. The network also promotes a new common metadata schema and content exchange format. Content reuse and content exchange is made possible by StreamOnTheFly in several use cases

Propelling the Potential of Enterprise Linked Data in Austria. Roadmap and Report

In times of digital transformation and considering the potential of the data-driven economy, it is crucial that data is not only made available, data sources can be trusted, but also data integrity can be guaranteed, necessary privacy and security mechanisms are in place, and data and access comply with policies and legislation. In many cases, complex and interdisciplinary questions cannot be answered by a single dataset and thus it is necessary to combine data from multiple disparate sources. However, because most data today is locked up in isolated silos, data cannot be used to its fullest potential. The core challenge for most organisations and enterprises in regards to data exchange and integration is to be able to combine data from internal and external data sources in a manner that supports both day to day operations and innovation. Linked Data is a promising data publishing and integration paradigm that builds upon standard web technologies. It supports the publishing of structured data in a semantically explicit and interlinked manner such that it can be easily connected, and consequently becomes more interoperable and useful. The PROPEL project - Propelling the Potential of Enterprise Linked Data in Austria - surveyed technological challenges, entrepreneurial opportunities, and open research questions on the use of Linked Data in a business context and developed a roadmap and a set of recommendations for policy makers, industry, and the research community. Shifting away from a predominantly academic perspective and an exclusive focus on open data, the project looked at Linked Data as an emerging disruptive technology that enables efficient enterprise data management in the rising data economy. Current market forces provide many opportunities, but also present several data and information management challenges. Given that Linked Data enables advanced analytics and decision-making, it is particularly suitable for addressing today's data and information management challenges. In our research, we identified a variety of highly promising use cases for Linked Data in an enterprise context. Examples of promising application domains include "customization and customer relationship management", "automatic and dynamic content production, adaption and display", "data search, information retrieval and knowledge discovery", as well as "data and information exchange and integration". The analysis also revealed broad potential across a large spectrum of industries whose structural and technological characteristics align well with Linked Data characteristics and principles: energy, retail, finance and insurance, government, health, transport and logistics, telecommunications, media, tourism, engineering, and research and development rank among the most promising industries for the adoption of Linked Data principles. In addition to approaching the subject from an industry perspective, we also examined the topics and trends emerging from the research community in the field of Linked Data and the Semantic Web. Although our analysis revolved around a vibrant and active community composed of academia and leading companies involved in semantic technologies, we found that industry needs and research discussions are somewhat misaligned. Whereas some foundation technologies such as knowledge representation and data creation/publishing/sharing, data management and system engineering are highly represented in scientific papers, specific topics such as recommendations, or cross-topics such as machine learning or privacy and security are marginally present. Topics such as big/large data and the internet of things are (still) on an upward trajectory in terms of attention. In contrast, topics that are very relevant for industry such as application oriented topics or those that relate to security, privacy and robustness are not attracting much attention. When it comes to standardisation efforts, we identified a clear need for a more in-depth analysis into the effectiveness of existing standards, the degree of coverage they provide with respect the foundations they belong to, and the suitability of alternative standards that do not fall under the core Semantic Web umbrella. Taking into consideration market forces, sector analysis of Linked Data potential, demand side analysis and the current technological status it is clear that Linked Data has a lot of potential for enterprises and can act as a key driver of technological, organizational, and economic change. However, in order to ensure a solid foundation for Enterprise Linked Data include there is a need for: greater awareness surrounding the potential of Linked Data in enterprises, lowering of entrance barriers via education and training, better alignment between industry demands and research activities, greater support for technology transfer from universities to companies. The PROPEL roadmap recommends concrete measures in order to propel the adoption of Linked Data in Austrian enterprises. These measures are structured around five fields of activities: "awareness and education", "technological innovation, research gaps, standardisation", "policy and legal", and "funding". Key short-term recommendations include the clustering of existing activities in order to raise visibility on an international level, the funding of key topics that are under represented by the community, and the setup of joint projects. In the medium term, we recommend the strengthening of existing academic and private education efforts via certification and to establish flagship projects that are based on national use cases that can serve as blueprints for transnational initiatives. This requires not only financial support, but also infrastructure support, such as data and services to build solutions on top. In the long term, we recommend cooperation with international funding schemes to establish and foster a European level agenda, and the setup of centres of excellence

Vitamin D Enhances Immune Effector Pathways of NK Cells Thus Providing a Mechanistic Explanation for the Increased Effectiveness of Therapeutic Monoclonal Antibodies

Patients with diffuse large cell lymphoma who have an adequate vitamin D supply derive significantly more benefit from immuno-chemotherapy with rituximab than patients with vitamin D deficiency; this is especially true for female patients. We have already been able to show that vitamin D increases the antibody-dependent cytotoxicity (ADCC) of NK cells in a sex-dependent manner, but it is unclear how vitamin D makes NK cells more efficient. Methods: Healthy individuals with vitamin D deficiency were supplemented with vitamin D to sufficient levels. NK cells were isolated from blood samples before and after vitamin D saturation. For transcriptome analysis, we used the Affymetrix Gene-Chip 2.0™. Gene expression analysis as well as supervised and unsupervised pathway analysis were performed. Results: Among others the “NK cell-associated cytotoxicity pathway” increased after vitamin D substitution. Five IFN-α subtypes (2, 4, 6, 7 and 10) and IFN-κ were more highly expressed and are mainly responsible in these pathways. In contrast, the pathway “interferon-gamma response”, as well as other sets in cytokine production and chemotaxis showed a reduction. Toll-like receptor genes (TLR-8, TLR-7, TLR-2) were downregulated and, therefore, are responsible for the decline of these pathways. The same could be shown for the “ubiquitin-ligase” pathway. Conclusions: Increased expression of several IFN-α subtypes may explain the increased ADCC of NK cells in vitamin D-replenished and otherwise healthy subjects. Other regulators of interferon production and ADCC are compensatory upregulated in compensation, such as Toll-like receptors and those of the ubiquitin ligase, and normalize after vitamin D substitution

Micromotives of Vote Switchers and Macrotransitions: The Case of the Immigration Issue in a Regional Earthquake Election in Germany 2018

Which issue-related motives underlie voters' decision to switch parties at the polls? Do switchers stick to the newly chosen party, or do they oscillate in a short-term way at intermediate elections? Relying on the behavioral theory of elections, we assumed aspiration-based voting of boundedly rational voters. We elicited issue-related switch and stay motives in an open-ended survey question format to identify the individual dominant aspirational frame. We traced the respondents' voting trajectories over three consecutive elections, including two state (2013 and 2018) elections in Bavaria (Germany) and one German federal election (2017). We focused on one of the most polarizing and salient issues in these elections, namely immigration. The case of reference is the 2018 Bavarian state election. Here, the incumbent majoritarian center-right party Christian Social Union tried to deter the entry of the right-wing populist party Alternative for Germany by adapting to it on the immigration issue in tone and position. The selected case allows assessment of the impact of issue-based adaptive behavior of the incumbent party at the level of the voters' switch or stay choices. We estimated the direction and number of voter flows for two interelection sequences of different lengths between different types of polls (federal and state). Our transition estimates are based on the hybrid multinomial Dirichlet model, a new technique integrating individual-level survey data and official aggregate data. Our estimates uncover substantial behavioral differences in the immigration issue public