FU survey Darmgezondheid (GSRS)
For the Leiden Longevity Study, long-lived siblings of European descent were recruited together with their offspring and the partners of this offspring between 2002 and 2006. Families were recruited if at least two long-lived siblings were alive and fulfilled the age criterion of 89 years or older for males and 91 years or older for females, representing less than 0.5% of the Dutch population in 2001 (Schoenmaker et al 2006, doi: [10.1038/sj.ejhg.5201508](http://https://www.nature.com/articles/5201508); Westendorp et al 2009, doi: [10.1111/j.1532-5415.2009.02381.x](http://https://agsjournals.onlinelibrary.wiley.com/doi/10.1111/j.1532-5415.2009.02381.x)). In total 944 long-lived siblings were included with a mean age of 94 years (range 89-104), 1671 offspring (61 years, 34-81) and 744 partners (60 years, 30-79). It is family based study consists of 1671 offspring of 421 nonagenarians sibling pairs of Dutch descent, and their 744 partners. Of all LLS participants HRC1.1 imputed genotypes are available.
LLS_IOP3_OLINKcardiomatebolic_metadata
From the group of 343 couples (Ntotal=686_ LLS PartnerOffspring that participated in the LLS between 2006 and 2008, 500 participants were examined for the third time between 2009 and 2010. In total 250 offspring-partners couples participated, with a mean age of 66 years. Fasted blood was drawn and serum/plasma and viable PBMCs were isolated and stored. All participant were subjected to cognitive tests (ACS-90, STROOP, Picture Word Learning test, LOT, Apathy scale, CES-D), and in 367 participants 3Tesla brain MRI scans were performed and of 341 participants CT-scan of abdomen was performed.
FU survey Gevoel en gedrag (CES-D)
FU_Castor_Thuis_vragenlijsten
Global Metabolomics
SignalingLipids Overview
Global Metabolomics Overview
FU Castor Balanstesten
LLS IOP3 Participant info
LLS IOP2 Nightingale QL16-20
From the group of 2,415 LLS PartnerOffspring that participated in the LLS between 2002 and 2006, 686 participants were examined for the second time between 2006 and 2008. In total 343 offspring and their partners (as couples living together) participated, with a mean age of 63 years. Of the 286 participants of the morning program, fasted blood was collected and serum/plasma was stored. Furthermore, skin replica’s and skin biopties were taken, from which viable fibroblasts were isolated and stored. The morning group was also subjected to an oral-glucose tolerance test. Of the 400 participants of the afternoon program, non-fasted blood was collected and serum/plasma and viable PBMCs were isolated and stored. The full blood was stimulated with LPS and cytokine levels were measured. From the majority of the total participants physical measures, DXA scan and standardized photographs of the face were taken, and all participants brought first morning void of urine which was stored.
LLS_IOP1_partoffs_Demography
For the Leiden Longevity Study, long-lived siblings of European descent were recruited together with their offspring and the partners of the offspring between 2002 and 2006. Families were recruited if at least two long-lived siblings were alive and fulfilled the age criterion of 89 years or older for males and 91 years or older for females, representing less than 0.5% of the Dutch population in 2001 (Schoenmaker et al 2006, doi: 10.1038/sj.ejhg.5201508; Westendorp et al 2009, doi: 10.1111/j.1532-5415.2009.02381.x). In total 944 long-lived siblings were included with a mean age of 94 years (range 89-104), 1671 offspring (61 years, 34-81) and 744 partners (60 years, 30-79) as population based controls. It is family based study consists of 1671 offspring of 421 nonagenarians sibling pairs of Dutch descent, and their 744 partners. The dataset of the LLS IOP1 Partner Offspring consists of the 1671 offspring of nonagenarian siblings and their 744 partners from 421 families of whom we have physical measurements, biosamples, biomarkers, and questionnaire data. We followed this group of 2,415 middle-aged participants for their vital status till 2020, for their morbidity status till 2017.
LLS IOP3 Partoffs Apolipoprotein platform
Plasma endothelial markers
FU survey Fysieke activiteit (SQUASH)
FU Castor Metingen handknijpkrachttest
SignalingLipids Metabolomics
BEAT COVID Severity Score LUMC
BEAT COVID Severity Score LUMC: Research laboratory data of LUMC BEAT COVID cohort. Prospective observational WMO study including 191 COVID-19 patients from April 2020 to March 2021. Over 400 different laboratory variables were measured, listed in the attached tables. Principle Investigator, Anna Roukens, LUCID. Website: https://w3id.org/lumc/lucid/beatcovid_severityscores
COVID-19
Anna Roukens, Principle Investigator, Dept. LUCID, https://orcid.org/0000-0002-1397-0992
Leiden University Medical Center, the Netherlands
Anna Roukens, , Principal Investigator of the LUMC BEAT COVID group
FU Castor Metingen algemeen
LLS IOP3 Nightingale QL16-20
Cognition_questions
IOP2_Partoffs
FU survey Kwaliteit van leven (EQ-5D)
Global Metabolomics Dictionary
FU Castor Medicatiegebruik
Clinicalchemistry
For the Leiden Longevity Study, long-lived siblings of European descent were recruited together with their offspring and the partners of the offspring between 2002 and 2006. Families were recruited if at least two long-lived siblings were alive and fulfilled the age criterion of 89 years or older for males and 91 years or older for females, representing less than 0.5% of the Dutch population in 2001 (Schoenmaker et al 2006, doi: 10.1038/sj.ejhg.5201508; Westendorp et al 2009, doi: 10.1111/j.1532-5415.2009.02381.x). In total 944 long-lived siblings were included with a mean age of 94 years (range 89-104), 1671 offspring (61 years, 34-81) and 744 partners (60 years, 30-79). It is family based study consists of 1671 offspring of 421 nonagenarians sibling pairs of Dutch descent, and their 744 partners. The dataset of the LLS IOP1 Nonagenarian Siblings consists of 944 long-lived siblings from 421 families of whom we have biosamples, biomarkers, and questionnaire data. We followed these nonagenarian participants for their vital status till 2020.
LLS IOP2 Gripstrength
Castor Medische voorgeschiedenis CCI
LLS IOP2 blood pressure
FU Castor Metingen Longfunctie
BEAT COVID Lab results LUMC
BEAT COVID Lab results LUMC: Research laboratory data of LUMC BEAT COVID cohort. Prospective observational WMO study including 191 COVID-19 patients from April 2020 to March 2021. Over 400 different laboratory variables were measured, listed in the attached tables. Principle Investigator, Anna Roukens, LUCID. Website: https://w3id.org/lumc/lucid/beatcovid_labmeasurements
Gut Microbiome related data
LLS_IOP1_partoffs_Participant_info
Q1 FFQ Nevo2006
Demography
FU Castor Thuis biomateriaal
LLS IOP2 BIA Body Composition
Q1 FFQ Food group key
Castor Metingen ECG
LLS Follow Up study
Visit measures
Cell counts
Clinical Chemistry
Cellcounts
Leiden NMR
Q1 FFQ Fooditems
FU Castor Bloedafname
BEAT COVID Viral Ct
BEAT COVID Viral Ct: Research laboratory data of LUMC BEAT COVID cohort. Prospective observational WMO study including 191 COVID-19 patients from April 2020 to March 2021. Over 400 different laboratory variables were measured, listed in the attached tables. Principle Investigator, Anna Roukens, LUCID. Website: https://w3id.org/lumc/lucid/beatcovid_viralct
Q1 FFQ Macronutrients
FU survey Alg vragenlijst LLS
Participant information
Nightingale
Survey Levensorientatie vragenlijst
Q1 FFQ Foodgroups main
IOP3_Partoffs
LLS_IOP1_partoffs_LeidenNMR_Kimble
SignalingLipids Dictionary
LLS Questionnaire 1
MRI Data
Castor Cognitietesten
LLS_IOP1_Partoffs_Nightingale
LLS IOP2 Participant info
FU Castor Metingen BIA meting
Q1_FFQ_Aminoacids
IOP1_Partoffs
FU Castor Scores questionair toeval
IGF axis
LLS_IOP3_OLINKcardiomatebolic_samples
FU Castor Metingen bloeddruk
FU survey Fysieke functie ADL IADL
Thyroid measures
LLS IOP2 Clinical chemistry
LLS_IOP3_OLINKcardiomatebolic_measures
Q1 FFQ key food groups 20200911
Q1 FFQ Foodgroups sub
IOP1_Sibs
FU Castor Welkom
FU survey Voedingsvragenlijst (FFQ)
FU survey Fysieke activeit (SQUASH) OUD
BEAT COVID Info LUMC
BEAT COVID Info LUMC: Research laboratory data of LUMC BEAT COVID cohort. Prospective observational WMO study including 191 COVID-19 patients from April 2020 to March 2021. Over 400 different laboratory variables were measured, listed in the attached tables. Principle Investigator, Anna Roukens, LUCID. Website: https://w3id.org/lumc/lucid/beatcovid_info
Plasma Amyloid markers
COMODULATE Lab results LUMC
COMODULATE Lab results LUMC: Research laboratory data of the LUMC COMODULATE cohort. Retrospective observational non-WMO study including COVID-19 and Influenza patients with and without ARDS from 2019 to 2024. Host transcriptomics and inflammatory proteomics variables were measured in respiratory samples. Principle Investigator, Jutte JC de Vries, LUCID. Website: https://w3id.org/lumc/lucid/comodulate_labmeasurements
Influenza
transcriptomics
Jutte J.C. de Vries, Principle Investigator, Dept. LUCID, https://orcid.org/0000-0003-2530-6260
Jutte J.C. de Vries, Principal Investigator
EuCanImage_GUMED_UC8
Within the EuCanImage project (https://eucanimage.eu/), imaging datasets are collected from multiple sites to facilitate the use of AI for cancer research. The BMIA XNAT will be used as main image data storage platform for centralized storage. As first usecase, breast cancer was identified, for which the first datasets will be collected from the University of Barcelona. The data will first be available to partners within the consortium, but will potentially be publicly released
AILS
Retrospective analysis of atypical iso intense lesions after Primovist injection
Brain_MRI_WML_ERASMUS
This collection will include brain MRI scans on which the amount of white matter lesions (WML) will be quantified.
CIRGUIDANCERadiomics Zuyderland Ziekenhuis
In this study, we aim to use a non-invasive radiomics alternative to predict the lymph node stage in patients with non-metastatic muscle-invasive bladder cancer. To this end, we will use the already gathered computed tomography (CT) data from the previously performed multicenter CIRGUIDANCE study. We would like to use the Trait XNAT to share the data among the hospitals.
Nivel Primary Care General Practices 2012
Electronic health record data from general practices spread throughout the Netherlands. General practice care comprises regular healthcare provision during normal practice hours, excluding out-of-hours primary care, emergency care and hospital admissions
EHR
Electronic Health Records EHR
Primary Care
Routine Healthcare Data
DEFENCE: Determination and Evaluation of the Frequency and Effects of myocardial damage iN patients with a SARS-CoV-2 infEction
Acute myocardial infarction
COVID-19 patient grouping
COVID-19 phase
Cardiac arrhythmia unspecified
Cerebrovascular diseases I60-I69
GP care
Heart failure
Myocarditis unspecified
home care
hospital care
human disease
national
CVON MIND AF
Brein MRIs van patiënten met permanent AF
EXCEPTIUS : Exceptional powers in time of Sars -CoV-2
international
national care public health measures
other
regional
target group of policy interventions
BIGR[eye] EMC
Data collected within the eye research group of the Biomedical Imaging Group Rotterdam, Erasmus MC
EGD
FOR ACCESS TO THE DATASET: Do not request an account directly through the XNAT portal. If you would like to access the dataset please send an email to: servicedesk@health-ri.nl You will then be asked to sign the data usage agreement, and an account will be created for you. ACCESS REQUESTS DIRECTLY THROUGH THE XNAT PORTAL WILL NOT BE CONSIDERED. The Erasmus Glioma Database (EGD) is a collection of 774 patients with glioma. For this patients pre-operative imaging, genetic and histological data, and tumor segmentations are available. See the license for all conditions: check the file 'data_license.pdf' at Resources > PROJECT_DATA Some scans might have a poor image quality or errors due to registration issues. We have marked this scans as 'unacceptable' scan quality. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952103
Waarderend onderzoeken en ontwikkelen: leidt de toepassing van deze interventie in de teams van de Stichting Jeugdgezondheidszorg Zuid-Holland West tot het versterken en waarborgen van de mentale vitaliteit van medewerkers?
Timing and sequence of vaccination against COVID-19 and Influenza
Codes for special purposes U00-U85
people by age
Lanadelumab for Treatment of COVID-19 Disease
COVID-19 U07.1
health care phase
Healthcare utilization in primary care during the corona pandemic: a nation-wide population-based study from a patient and healthcare provider perspective
Cerebral infarction
AFRICAI_MICCAI2024_CTSpine1K
Collection of data from the MICCAI 2024 CTSpine1K Dataset as part of the EuCanImage sponsored AFRICAI repository. In this repository, we introduce a large-scale spine CT dataset called CTSpine1K, curated from multiple sources for vertebra segmentation, which contains 1,005 CT volumes with over 500,000 labeled vertebrae slices and 11,172 vertebrae belonging to different spinal conditions. The data within this work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0) If you use our dataset, please cite our paper: Yang Deng, Ce Wang, Yuan Hui, et al. CtSpine1k: A large-scale dataset for spinal vertebrae segmentation in computed tomography. arXiv preprint arXiv:2105.14711 (2021).
Dataset
Image
Medical
Segmentation
Spine
Caging the dragon: translational approach to unravel and prevent COVID-19 associated thrombosis (10430012010004)
COVID-19 vaccination grouping
Diseases of veins lymphatic vessels and lymph nodes not elsewhere classified I80-I89
Pulmonary heart disease and diseases of pulmonary circulation I26-I28
local
nursing home care
outpatient care
residential care
Een onverwachte valse start op de arbeidsmarkt
Effects COVID on participation
people by education
Economische Veerkracht van Regio's