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- 2019
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Journal article (peer-reviewed)
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- Dramburg, S, et al.
(author)
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EAACI Molecular Allergology User's Guide 2.0
- 2023
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In: Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology. - 1399-3038. ; 3434 Suppl 28, s. e13854-
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Journal article (peer-reviewed)
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- Laurie, Steven, et al.
(author)
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The RD-Connect Genome-Phenome Analysis Platform : Accelerating diagnosis, research, and gene discovery for rare diseases
- 2022
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In: Human Mutation. - : John Wiley & Sons. - 1059-7794 .- 1098-1004. ; 43:6, s. 717-733
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Journal article (peer-reviewed)abstract
- Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes.
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- Schaap, M., et al.
(author)
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Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms
- 2009
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In: Medical Image Analysis. - : Elsevier. - 1361-8415 .- 1361-8423. ; 13:5, s. 701-714
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Journal article (peer-reviewed)abstract
- Efficiently obtaining a reliable coronary artery centerline from computed tomography angiography data is relevant in clinical practice. Whereas numerous methods have been presented for this purpose, up to now no standardized evaluation methodology has been published to reliably evaluate and compare the performance of the existing or newly developed coronary artery centerline extraction algorithms. This paper describes a standardized evaluation methodology and reference database for the quantitative evaluation of coronary artery centerline extraction algorithms. The contribution of this work is fourfold: (1) a method is described to create a consensus centerline with multiple observers, (2) well-defined measures are presented for the evaluation of coronary artery centerline extraction algorithms, (3) a database containing 32 cardiac CTA datasets with corresponding reference standard is described and made available, and (4) 13 coronary artery centerline extraction algorithms, implemented by different research groups, are quantitatively evaluated and compared. The presented evaluation framework is made available to the medical imaging community for benchmarking existing or newly developed coronary centerline extraction algorithms.
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