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ShareScore release 0.9.0
Dataset results
184 results for “personalisation”
Data from: Sudden unexpected death in epilepsy: a personalised prediction tool
<div> <strong>Objective: </strong>To develop and validate a tool for individualised prediction of Sudden Unexpected Death in Epilepsy (SUDEP) risk, we re-analysed data from one cohort and three case-control studies undertaken 1980-2005.</div> <p><span><strong>Methods:</strong><span><strong> </strong>We entered 1273 epilepsy cases (287 SUDEP, 986 controls) and 22 clinical predictor variables into a Bayesian logistic regression model.</span></span></p> <p><strong>Results:</strong> Cross-validated individualized model predictions were superior to baseline models developed from only average population risk or from generalised tonic-clonic seizure frequency (pairwise difference in leave-one-subject-out expected log posterior density = 35.9, SEM +/-12.5, and 22.9, SEM +/-11.0 respectively). The mean cross-validated (95% Credibility Interval) Area Under the Receiver Operating Curve was 0.71 (0.68 to 0.74) for our model versus 0.38 (0.33 to 0.42) and 0.63 (0.59 to 0.67) for the baseline average and generalised tonic-clonic seizure frequency models respectively. Model performance was weaker when applied to non-represented populations. Prognostic factors included generalized tonic-clonic and focal-onset seizure frequency, alcohol excess, younger age of epilepsy onset and family history of epilepsy. Anti-seizure medication adherence was associated with lower risk.</p> <p><strong>Conclusions:</strong> Even when generalised to unseen data, model predictions are more accurate than population-based estimates of SUDEP. Our tool can enable risk-based stratification for biomarker discovery and interventional trials. With further validation in unrepresented populations it may be suitable for routine individualized clinical decision-making. Clinicians should consider assessment of multiple risk factors, and not only focus on the frequency of convulsions.</p>
Personalised Therapy for Metastatic ADPC Determined by Genetic Testing and Avatar Model Generation
ClinicalTrials.gov study NCT02795650. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Personalised Simulation Technologies for Optimising Treatment in the Intensive Care Unit
ClinicalTrials.gov study NCT04297397. IPD Sharing: NO. Countries: 1. Publications: 4.
Strategies for Personalised Nutrition
ClinicalTrials.gov study NCT01530139. IPD Sharing: YES. Countries: 7. Publications: 18.
Personalised Ablation Strategies in AF
ClinicalTrials.gov study NCT05633303. IPD Sharing: NO. Countries: 1. Publications: 1.
Personalised Exercise Rehabilitation for Cancer Survivorship
ClinicalTrials.gov study NCT05615285. IPD Sharing: NO. Countries: 1. Publications: 3.
Personalised Multicomponent Exercise Programme in Peripheral Arterial Disease
ClinicalTrials.gov study NCT06410521. IPD Sharing: NO. Countries: 1. Publications: 5.
Behaviour-focused Personalised Nutrition Intervention
ClinicalTrials.gov study NCT06631469. IPD Sharing: NO. Countries: 1. Publications: 4.
Design of Personalised SupplemenTs Based on the Gut MicRobiota Through Artificial Intelligence for Alzheimer's Patients
ClinicalTrials.gov study NCT06199193. IPD Sharing: NO. Countries: 1. Publications: 1.
PICk-UP: PersonalIsed CommUnity-based Physical Activities for Patients With Chronic Obstructive Pulmonary Disease
ClinicalTrials.gov study NCT04223362. IPD Sharing: UNDECIDED. Countries: 1. Publications: 20.
pErsonalised Nocebo Assessment of Beta-blockEr Symptoms in Heart Failure
ClinicalTrials.gov study NCT07029906. IPD Sharing: UNDECIDED. Countries: 1. Publications: 3.
Personalising Psychotherapy for Chronic Primary Pain Using Network Analysis
ClinicalTrials.gov study NCT06179784. IPD Sharing: UNDECIDED. Countries: 1. Publications: 21.
Patient Empowerment Through Predictive Personalised Decision Support (PEPPER)
ClinicalTrials.gov study NCT03186300. IPD Sharing: UNDECIDED. Countries: 1. Publications: 19.
Artificial Intelligence Driven Personalisation of Radiotherapy and Concomitant Androgen Deprivation Therapy for Prostate Cancer Patients (the HypoPro Trial)
ClinicalTrials.gov study NCT06772441. IPD Sharing: NO. Countries: 1. Publications: 5.
Personalising Anti-TNF Therapy in Crohns Disease (PANTS)
ClinicalTrials.gov study NCT03088449. IPD Sharing: YES. Countries: 1. Publications: 3.
Personalised Treatment for OSA
ClinicalTrials.gov study NCT06915077. IPD Sharing: NO. Countries: 1. Publications: 1.
Investigating National Solutions for Personalised Iodine-131 Radiation Exposure
ClinicalTrials.gov study NCT04391244. IPD Sharing: NO. Countries: 1. Publications: 1.
Personalisation of Prosthetic Care for Lower- Limb Amputees
ClinicalTrials.gov study NCT06243549. IPD Sharing: NO. Countries: 1. Publications: 1.
Effect of Personalised Citizen Assistance for Social Participation(APIC) on Older Adults Health and Social Participation
ClinicalTrials.gov study NCT03161860. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Innovative Approaches for Personalised Cardiovascular Prevention
ClinicalTrials.gov study NCT05883878. IPD Sharing: NO. Countries: 1. Publications: 1.
ScienceDex guides
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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.