Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
111
datasets available to search
ShareScore release 0.9.0
Dataset results
111 results for “EHR”
Effectively controlling for sample relatedness in large-scale GWAS: application to 79 EHR-derived longitudinal traits
<p><span>Sample relatedness is a major confounder in genome-wide association studies (GWAS), potentially leading to inflated type I error rates if not appropriately controlled. A common strategy is to incorporate a random effect related to genetic relatedness matrix (GRM) into regression models. However, this approach is challenging for large-scale GWAS of complex traits, such as longitudinal traits. Here we propose a scalable and accurate analysis framework, SPA<sub>GRM</sub>, which controls for sample relatedness via a precise approximation of the joint distribution of genotypes. SPA<sub>GRM</sub> can utilize GRM-free models and thus is applicable to various trait types and statistical methods, including linear mixed models and generalized estimation equations for longitudinal traits. A hybrid strategy incorporating saddlepoint approximation greatly increases the accuracy to analyze low-frequency and rare genetic variants, especially in unbalanced phenotypic distributions. We also introduce SPA<sub>GRM(CCT)</sub> to aggregate the results following different models via Cauchy combination test. Extensive simulations and real data analyses demonstrated that SPA<sub>GRM</sub> maintains well-controlled type I error rates and SPA<sub>GRM(CCT)</sub> can serve as a broadly effective method. Applying SPA<sub>GRM</sub> to 79 longitudinal traits extracted from</span><span> </span><span>UK Biobank primary care data, we identified 7,463 genetic loci, making a pioneering attempt to conduct GWAS for these traits as longitudinal traits.</span></p>
Text-fig. 1. Geographic position of the beaver-bearing sites discussed in this paper. Red triangles – records of Castor, blue dots – records of Trogontherium. Bilz II – Bilzingsleben II, Ehr – Weimar-Ehringsdorf, Mosb 2 – Mosbach 2, Taub – Weimar-Taubach, Teg – Tegelen. (This map was created using ArcGIS® software by Esri. ArcGIS® and ArcMap™ are the intellectual property of Esri and are used herein under license. Copyright © Esri). in Mortality Profiles Of Castor And Trogontherium (Mammalia: Rodentia, Castoridae), With Notes On The Site Formation Of The Mid-Pleistocene Hominin Locality Bilzingsleben Ii (Thuringia, Central Germany)
Text-fig. 1. Geographic position of the beaver-bearing sites discussed in this paper. Red triangles – records of Castor, blue dots – records of Trogontherium. Bilz II – Bilzingsleben II, Ehr – Weimar-Ehringsdorf, Mosb 2 – Mosbach 2, Taub – Weimar-Taubach, Teg – Tegelen. (This map was created using ArcGIS® software by Esri. ArcGIS® and ArcMap™ are the intellectual property of Esri and are used herein under license. Copyright © Esri).
EXPLICATIOxN DE LA PLANCHE 4. Fig. 1. Scaridium longicaudum Ehr., vue latérale. Gross. 320. Fig. 2. Diglena forcipata Ehr., vue dorsale. Gross. 320. Fig. 3. Salpina mucronata Ehr., vue latérale. Gross. 320. Fig. 4. Salpina brevispina Ehr., vue dorsale. Gross. 320. Fig. -T. Dinocharis pocillum Ehr., vue dorsale. Gross. 320. Fig. 6. Copeus labiatiis Gosse, vue dorsale. Gross. 175. in Note sur quelques mâles de Rotateurs
EXPLICATIOxN DE LA PLANCHE 4. Fig. 1. Scaridium longicaudum Ehr., vue latérale. Gross. 320. Fig. 2. Diglena forcipata Ehr., vue dorsale. Gross. 320. Fig. 3. Salpina mucronata Ehr., vue latérale. Gross. 320. Fig. 4. Salpina brevispina Ehr., vue dorsale. Gross. 320. Fig. -T. Dinocharis pocillum Ehr., vue dorsale. Gross. 320. Fig. 6. Copeus labiatiis Gosse, vue dorsale. Gross. 175.
The benefit of augmenting open data with clinical data-warehouse EHR for forecasting SARS-CoV-2 hospitalizations in Bordeaux area, France
<p><strong>Objective</strong></p> <p>The aim of this study was to develop an accurate regional forecast algorithm to predict the number of hospitalized patients and to assess the benefit of the Electronic Health Records (EHR) information to perform those predictions. Materials and Methods Aggregated data from SARS-CoV-2 and weather public database and data warehouse of the Bordeaux hospital were extracted from May 16, 2020, to January 17, 2022. The outcomes were the number of hospitalized patients in the Bordeaux Hospital at 7 and 14 days. We compared the performance of different data sources, feature engineering, and machine learning models.</p> <p><strong>Results </strong></p> <p>During the period of 88 weeks, 2561 hospitalizations due to COVID-19 were recorded at the Bordeaux Hospital. The model achieving the best performance was an elastic-net penalized linear regression using all available data with a median relative error at 7 and 14 days of 0.136 [0.063; 0.223] and 0.198 [0.105; 0.302] hospitalizations, respectively. Electronic health records (EHRs) from the hospital data warehouse improved median relative error at 7 and 14 days by 10.9% and 19.8%, respectively. Graphical evaluation showed remaining forecast error was mainly due to delay in slope shift detection.</p> <p><strong>Discussion </strong></p> <p>Forecast models showed overall good performance both at 7 and 14 days which was improved by the addition of the data from Bordeaux Hospital data warehouse.</p> <p><strong>Conclusions </strong></p> <p>The development of hospital data warehouses might help to get more specific and faster information than traditional surveillance systems, which in turn will help to improve epidemic forecasting at a larger and finer scale.</p>
Improving Providers' Decision-Making and Reducing Information Overload Using Information Visualization in EHRs
ClinicalTrials.gov study NCT05937646. IPD Sharing: YES. Countries: 1. Publications: 1.
The benefit of augmenting open data with clinical data-warehouse EHR for forecasting SARS-CoV-2 hospitalizations in Bordeaux area, France
Open the record for dataset details and reuse information.
Longitudinal trends of EHR concepts in pediatric patients
<p>The longitudinal nature of the data motivated temporal trend identification in the pediatric EHR datatypes. Over the past three decades (1980-2018), we identified and quantified the temporal trend of 16,460 EHR concepts across measurement, visit, diagnosis, drug, and procedure datatypes. </p>
Enhanced, EHR-facilitated Cancer Symptom Control Pragmatic Clinical Trial
ClinicalTrials.gov study NCT03892967. IPD Sharing: Not stated. Countries: 1. Publications: 7.
Assessing the Performance of Artificial Intelligence (AI)-Augmented Electronic Health Record (EHR) Data Abstraction for Clinical Trial Patient Screening
ClinicalTrials.gov study NCT06561217. IPD Sharing: NO. Countries: 1. Publications: 1.
EHR-Based and Fax-Based Referral to a Tobacco Quitline: A Comparative Study
ClinicalTrials.gov study NCT02735382. IPD Sharing: NO. Countries: 1. Publications: 2.
NUDGE-EHR Replication Trial at Mass General Brigham
ClinicalTrials.gov study NCT05538065. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Randomized Trial of a BE-EHR Module to Guide the Care of Older Adults With Diabetes
ClinicalTrials.gov study NCT04181307. IPD Sharing: YES. Countries: 1. Publications: 2.
COVID EHR COHORT at the University of Wisconsin
ClinicalTrials.gov study NCT04506528. IPD Sharing: YES. Countries: 1. Publications: 3.
EHR-based Decision Support for Pediatric Acute Abdominal Pain in Emergency Care
ClinicalTrials.gov study NCT02633735. IPD Sharing: NO. Countries: 1. Publications: 2.
Nudging Provider Adoption of Clinical Decision Support: Implementation of an EHR-Agnostic Pulmonary Embolism Risk Prediction Tool
ClinicalTrials.gov study NCT07249385. IPD Sharing: YES. Countries: 1. Publications: 0.
Behavioral Economics Applications to Geriatrics Leveraging EHRs R33 Trial
ClinicalTrials.gov study NCT04289753. IPD Sharing: NO. Countries: 1. Publications: 1.
Addressing Antihypertensive Medication Adherence Through EHR-enabled Teamlets in Primary Care
ClinicalTrials.gov study NCT05349422. IPD Sharing: YES. Countries: 1. Publications: 4.
EHR-Based Medication Complete Communication Strategy to Promote Safe Opioid Use
ClinicalTrials.gov study NCT02431793. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Assessing Effectiveness and Implementation of an EHR Tool to Assess Heart Health Among Survivors
ClinicalTrials.gov study NCT03935282. IPD Sharing: YES. Countries: 1. Publications: 109.
Behavioral Economics to Improve Flu Vaccination Using EHR Nudges
ClinicalTrials.gov study NCT06057727. IPD Sharing: YES. Countries: 1. Publications: 2.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.