Background Medical Image segmentation is an important image processing step. Comparing images to evaluate the quality of segmentation is an essential part of measuring progress in this research area. Some of the challenges in evaluating medical segmentation are: metric selection, the use in the literature of multiple definitions for certain metrics, inefficiency of the metric calculation implementations leading to difficulties with large volumes, and lack of support for fuzzy segmentation by existing metrics. Result First we present an overview of 20 evaluation metrics selected based on a comprehensive literature review. For fuzzy segmentation, which shows the level of membership of each voxel to multiple classes, fuzzy definitions of all metrics are provided. We present a discussion about metric properties to provide a guide for selecting evaluation metrics. Finally, we propose an efficient evaluation tool implementing the 20 selected metrics. The tool is optimized to perform efficiently in terms of speed and required memory, also if the image size is extremely large as in the case of whole body MRI or CT volume segmentation. An implementation of this tool is available as an open source project. Conclusion We propose an efficient evaluation tool for 3D medical image segmentation using 20 evaluation metrics and provide guidelines for selecting a subset of these metrics that is suitable for the data and the segmentation task. ; European Union Seventh Framework Programme (FP7/2007-2013) ; 1
In: Advances in Information Retrieval: 40th European Conference on IR Research, ECIR 2018, Grenoble, France, March 26-29, 2018 ; Proceedings, S. 563-569
Concepts are used to solve the term-mismatch problem. However, we need an effective similarity measure between concepts. Word embedding presents a promising solution. We present in this study three approaches to build concepts vectors based on words vectors. We use a vector-based measure to estimate inter-concepts similarity. Our experiments show promising results. Furthermore, words and concepts become comparable. This could be used to improve conceptual indexing process.
In March 2020, the Austrian government introduced a widespread lock-down in response to the COVID-19 pandemic. Based on subjective impressions and anecdotal evidence, Austrian public and private life came to a sudden halt. Here we assess the effect of the lock-down quantitatively for all regions in Austria and present an analysis of daily changes of human mobility throughout Austria using near-real-time anonymized mobile phone data. We describe an efficient data aggregation pipeline and analyze the mobility by quantifying mobile-phone traffic at specific point of interests (POIs), analyzing individual trajectories and investigating the cluster structure of the origin-destination graph. We found a reduction of commuters at Viennese metro stations of over 80% and the number of devices with a radius of gyration of less than 500 m almost doubled. The results of studying crowd-movement behavior highlight considerable changes in the structure of mobility networks, revealed by a higher modularity and an increase from 12 to 20 detected communities. We demonstrate the relevance of mobility data for epidemiological studies by showing a significant correlation of the outflow from the town of Ischgl (an early COVID-19 hotspot) and the reported COVID-19 cases with an 8-day time lag. This research indicates that mobile phone usage data permits the moment-by-moment quantification of mobility behavior for a whole country. We emphasize the need to improve the availability of such data in anonymized form to empower rapid response to combat COVID-19 and future pandemics.
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.
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.
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.
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.
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.
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]
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.