Политика заштите конкуренције у Србији (Protection of Competition Policy in Serbia)
In: Ekonomika, Band 60, Heft 1, S. 167-173
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In: Ekonomika, Band 60, Heft 1, S. 167-173
SSRN
Working paper
The full benefit from using AI to generate value for businesses, societal wellbeing and the environment is still to be fully realised. To lower adoption barriers of Industrial AI, challenges on multiple levels (technical complexity, trustworthiness, industrialisation, data frameworks and infrastructures, etc.) need to be addressed to benefit from its full socio economic potential for economy, society and welfare. It is now time to foster the development of "industrial and trustworthy AI" and nurture European innovation and sovereignty ambitions and benefit society and leading European industries. In this position paper, a comprehensive industrial and trustworthy AI framework that clusters the priority area for AI research, innovation and deployment is introduced. It covers tools and methodologies that support the design, test, validation, verification, and maintainability of AI based functions and systems and addresses the development of AI based process and systems to demonstrate its integration into new products and services. Conformity assessment schemes, balancing innovation, business and European perspectives, are considered to connect risk management, functional andtrustworthiness requirements to industrial processes. In addition adequate standards supporting industrial AI and trustworthiness will play a central role. Implementing the industrial and trustworthy AI framework will require resources beyond the means of any European private stakeholders. Therefore, strong support from ecosystems, governments, and Europe might not be an option but necessary.
BASE
The full benefit from using AI to generate value for businesses, societal wellbeing and the environment is still to be fully realised. To lower adoption barriers of Industrial AI, challenges on multiple levels (technical complexity, trustworthiness, industrialisation, data frameworks and infrastructures, etc.) need to be addressed to benefit from its full socio economic potential for economy, society and welfare. It is now time to foster the development of "industrial and trustworthy AI" and nurture European innovation and sovereignty ambitions and benefit society and leading European industries. In this position paper, a comprehensive industrial and trustworthy AI framework that clusters the priority area for AI research, innovation and deployment is introduced. It covers tools and methodologies that support the design, test, validation, verification, and maintainability of AI based functions and systems and addresses the development of AI based process and systems to demonstrate its integration into new products and services. Conformity assessment schemes, balancing innovation, business and European perspectives, are considered to connect risk management, functional andtrustworthiness requirements to industrial processes. In addition adequate standards supporting industrial AI and trustworthiness will play a central role. Implementing the industrial and trustworthy AI framework will require resources beyond the means of any European private stakeholders. Therefore, strong support from ecosystems, governments, and Europe might not be an option but necessary.
BASE
The full benefit from using AI to generate value for businesses, societal wellbeing and the environment is still to be fully realised. To lower adoption barriers of Industrial AI, challenges on multiple levels (technical complexity, trustworthiness, industrialisation, data frameworks and infrastructures, etc.) need to be addressed to benefit from its full socio economic potential for economy, society and welfare. It is now time to foster the development of "industrial and trustworthy AI" and nurture European innovation and sovereignty ambitions and benefit society and leading European industries. In this position paper, a comprehensive industrial and trustworthy AI framework that clusters the priority area for AI research, innovation and deployment is introduced. It covers tools and methodologies that support the design, test, validation, verification, and maintainability of AI based functions and systems and addresses the development of AI based process and systems to demonstrate its integration into new products and services. Conformity assessment schemes, balancing innovation, business and European perspectives, are considered to connect risk management, functional andtrustworthiness requirements to industrial processes. In addition adequate standards supporting industrial AI and trustworthiness will play a central role. Implementing the industrial and trustworthy AI framework will require resources beyond the means of any European private stakeholders. Therefore, strong support from ecosystems, governments, and Europe might not be an option but necessary.
BASE
In: Auffray , C , Balling , R , Barroso , I , Bencze , L , Benson , M , Bergeron , J , Bernal-Delgado , E , Blomberg , N , Bock , C , Conesa , A , Del Signore , S , Delogne , C , Devilee , P , Di Meglio , A , Eijkemans , M , Flicek , P , Graf , N , Grimm , V , Guchelaar , H J , Guo , Y K , Gut , I G , Hanbury , A , Hanif , S , Hilgers , R D , Honrado , Á , Hose , D R , Houwing-Duistermaat , J , Hubbard , T , Janacek , S H , Karanikas , H , Kievits , T , Kohler , M , Kremer , A , Lanfear , J , Lengauer , T , Maes , E , Meert , T , Müller , W , Nickel , D , Oledzki , P , Pedersen , B , Petkovic , M , Pliakos , K , Rattray , M , i Màs , J R , Schneider , R , Sengstag , T , Serra-Picamal , X , Spek , W , Vaas , L A I , van Batenburg , O , Vandelaer , M , Varnai , P , Villoslada , P , Vizcaíno , J A , Wubbe , J P M & Zanetti , G 2016 , ' Making sense of big data in health research : Towards an EU action plan ' , Genome medicine , vol. 8 , no. 1 , 71 . https://doi.org/10.1186/s13073-016-0323-y
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.
BASE
In: http://orbilu.uni.lu/handle/10993/28371
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.
BASE
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.
BASE
In: Auffray , C , Balling , R , Barroso , I , Bencze , L , Benson , M , Bergeron , J , Bernal-Delgado , E , Blomberg , N , Bock , C , Conesa , A , Del Signore , S , Delogne , C , Devilee , P , Di Meglio , A , Eijkemans , M , Flicek , P , Graf , N , Grimm , V , Guchelaar , H-J , Guo , Y-K , Gut , I G , Hanbury , A , Hanif , S , Hilgers , R-D , Honrado , Á , Hose , D R , Houwing-Duistermaat , J , Hubbard , T , Janacek , S H , Karanikas , H , Kievits , T , Kohler , M , Kremer , A , Lanfear , J , Lengauer , T , Maes , E , Meert , T , Müller , W , Nickel , D , Oledzki , P , Pedersen , B , Petkovic , M , Pliakos , K , Rattray , M , I Màs , J R , Schneider , R , Sengstag , T , Serra-Picamal , X , Spek , W , Vaas , L A I , van Batenburg , O , Vandelaer , M , Varnai , P , Villoslada , P , Vizcaíno , J A , Wubbe , J P M & Zanetti , G 2016 , ' Making sense of big data in health research : Towards an EU action plan ' Genome Medicine , vol 8 , no. 1 , pp. 71 . DOI:10.1186/s13073-016-0323-y
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.
BASE
In: Auffray , C , Balling , R , Barroso , I , Bencze , L , Benson , M , Bergeron , J , Bernal-Delgado , E , Blomberg , N , Bock , C , Conesa , A , Del Signore , S , Delogne , C , Devilee , P , Di Meglio , A , Eijkemans , M , Flicek , P , Graf , N , Grimm , V , Guchelaar , H J , Guo , Y K , Gut , I G , Hanbury , A , Hanif , S , Hilgers , R D , Honrado , Á , Hose , D R , Houwing-Duistermaat , J , Hubbard , T , Janacek , S H , Karanikas , H , Kievits , T , Kohler , M , Kremer , A , Lanfear , J , Lengauer , T , Maes , E , Meert , T , Müller , W , Nickel , D , Oledzki , P , Pedersen , B , Petkovic , M , Pliakos , K , Rattray , M , i Màs , J R , Schneider , R , Sengstag , T , Serra-Picamal , X , Spek , W , Vaas , L A I , van Batenburg , O , Vandelaer , M , Varnai , P , Villoslada , P , Vizcaíno , J A , Wubbe , J P M & Zanetti , G 2016 , ' Erratum to : Making sense of big data in health research: Towards an EU action plan [Genome Med., 8 (2016) (71)] ' , Genome medicine , vol. 8 , no. 1 , 118 . https://doi.org/10.1186/s13073-016-0376-y
The published article [1] has two points of confusion in the section entitled "Technical challenges related to the management of electronic health records". Firstly, the International Rare Diseases Research Consortium (IRDiRC) has developed policies and guidelines on approaches to data sharing meant to enable and improve the development of diagnoses and therapies for rare diseases. However, at present, IRDiRC has not developed best practices for the management of electronic health records (EHRs). Secondly, RARE-Bestpractices is a European Commission 7th Framework Programme (FP7) funded initiative, independent of IRDiRC. RARE-Bestpractices contributes to IRDiRC goals and objectives; however the initiative itself is not sponsored nor connected to IRDiRC.
BASE
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health arid healthcare for all Europearis. ; Funding Agencies|European Union [115568, 603160, 282510, 664691, 115749, 305033, 305397, 288028, 242189, 211601]; European Molecular Biology Laboratory; Wellcome Trust [WT098051]; [115372]; [257082]; [291814]; [291728]; [321567]; [262055]; [115446]; [602552]; [644753]; [634143]; [261357]; [305280]; [115525]; [2011 23 02]; [270089]; [278433]; [602525]; [201418]; [242135]; [260558]; [223411]; [305626]; [115621]; [611388]; [306000]; [354457]; [305564]; [115010]; [269978]
BASE
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.
BASE