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Dataset results
470 results for “prediction of disease”
Kroll et al., 2024. Behavioural pharmacology predicts disrupted signalling pathways and candidate therapeutics from zebrafish mutants of Alzheimer's disease risk genes
<p>Data repository for</p> <p>François Kroll, Joshua Donnelly, Joshua Donnelly, Güliz Gürel Özcan, Eirinn Mackay, Jason Rihel</p> <div> <div><strong>Behavioural pharmacology predicts disrupted signalling pathways and candidate therapeutics from zebrafish mutants of Alzheimer’s disease risk genes</strong></div> <br> <div>eLife, 2024.</div> <br> <div><a href="https://doi.org/10.7554/eLife.96839.1">https://doi.org/10.7554/eLife.96839.1</a></div> <div> </div> <div>Code is found in the <a href="https://github.com/francoiskroll/ZFAD">GitHub repository</a>. Please see notes there.</div> </div> <p>___</p> <p>Contact:</p> <p>Twitter: @francois_kroll</p> <p>Email: francois@kroll.be</p>
Clinical Dataset for the Paper 'Machine Learning Prediction of Treatment Response to Biological Disease-Modifying Antirheumatic Drugs in Rheumatoid Arthritis'
<p>This dataset accompanies the manuscript titled "Machine Learning Prediction of Treatment Response to Biological Disease-Modifying Antirheumatic Drugs in Rheumatoid Arthritis." It includes clinical data used for training and evaluating the machine learning models described in the paper. The dataset contains baseline clinical data of 154 RA patients who were treated with bDMARDs. The labels for remission, and effectiveness (remission and low disease activity) were applied after a 6-month follow-up based on EULAR criteria on DAS28ESR. The sustained effectiveness label indicates maintaining effectiveness within 6 months after initially achieving effectiveness.</p> <p><strong>Crossponder Authors:</strong></p> <ul> <li>Fatemeh Salehi (email: <a rel="noreferrer">fatemeh.salehihafshejni@fau.de</a>)</li> </ul>
Data from: Axial symptoms predict mortality in patients with Parkinson disease with subthalamic stimulation
Objective: To characterize how disease progression is associated with mortality in a large cohort of PD patients with long-term follow-up after STN-DBS. Methods: Motor and cognitive disabilities were assessed before, and 1, 2, 5 and 10 years after STN-DBS in 143 consecutive PD patients. We measured motor symptoms Off and On levodopa and STN-DBS, and recorded causes of death. We used linear mixed-models to characterize symptom progression, including interactions between treatment conditions and time to determine how treatments changed efficacy. We used joint models to link progression to mortality. Results: Median observation time was 12 years after surgery, during which akinesia, rigidity and axial symptoms worsened, with mean increases of 8.8 (SD 6.5), 1.8 (3.1) and 5.4 (4.1) points from year 1 to 10 after surgery (On dopamine/On STN-DBS), respectively. Responses to dopaminergic medication and STN-DBS were attenuated with time, but remained effective for all except axial symptoms, for which both treatments and their combination were predicted to be ineffective 20 years after surgery. Cognitive status significantly declined. Forty-one patients died with a median time to death of 9 years after surgery. The current level of axial disability was the only symptom that significantly predicted death (HR=4.30 [SE 1.50] per unit of square-root transformed axial score). Conclusions: We quantified long-term symptom progression and attenuation of dopaminergic medication and STN-DBS treatment efficacy in PD patients, and linked symptom progression to mortality. Axial disability significantly predicts individual risk of death after surgery, which may be useful for planning therapeutic strategies in PD.
Assessment of the Effect of Periodontal Disease Prediction System on Oral Hygiene Motivation
ClinicalTrials.gov study NCT06577246. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Prediction of Progression of Coronary Artery Disease (CAD) Using Vascular Profiling of Shear Stress and Wall Morphology
ClinicalTrials.gov study NCT01316159. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Predictive Value of Coronary Heart Disease (CHD) Biomarkers for CHD Death
ClinicalTrials.gov study NCT01864122. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Predictive Ability of the Chronic Obstructive Pulmonary Disease (COPD) Assessment Test (CAT) for Acute Exacerbations (PACE) in Patients With COPD
ClinicalTrials.gov study NCT01254032. IPD Sharing: YES. Countries: 4. Publications: 1.
Development of a Novel Risk Prediction Tool for Emergency Department Patients Symptoms of Coronary Artery Disease
ClinicalTrials.gov study NCT06743672. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Fractional Exhaled Nitric Oxide (FeNO) Result Prediction Factors in Children With Allergic Diseases
ClinicalTrials.gov study NCT00815984. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Predictive and Diagnostic Value of Tau and Beta-amyloid Markers in the Dementia of Parkinson's Disease
ClinicalTrials.gov study NCT02243982. IPD Sharing: Not stated. Countries: 1. Publications: 16.
Predicting Oxygen Desaturation in Chronic Obstructive Pulmonary Disease (COPD) Patients
ClinicalTrials.gov study NCT01303913. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Prediction Model of Cardiac Risk for Dental Extraction in Elderly Patients With Cardiovascular Diseases
ClinicalTrials.gov study NCT03211312. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Predictive Factors of Disease-free Survival After Complete Pathological Response to Neoadjuvant Radiotherapy in Rectal Adenocarcinoma
ClinicalTrials.gov study NCT03601689. IPD Sharing: UNDECIDED. Countries: 2. Publications: 1.
Predictive Value of Cognitive Tests Performed for the Diagnosis of Alzheimer's Disease and Related Disorders
ClinicalTrials.gov study NCT01316562. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Predictive Value of DICA in the Diverticular Disease of the Colon
ClinicalTrials.gov study NCT02758860. IPD Sharing: NO. Countries: 7. Publications: 2.
Prediction of Decompensation and HCC Development in Advanced Chronic Liver Disease
ClinicalTrials.gov study NCT06523608. IPD Sharing: UNDECIDED. Countries: 1. Publications: 41.
PREDICT Trial: PRospective Evaluation of NTM Disease In CysTic Fibrosis
ClinicalTrials.gov study NCT02073409. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Study of Biomarkers That Predict the Evolution of Huntington's Disease
ClinicalTrials.gov study NCT01412125. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Personalized Prediction Strategy for Acute Exacerbation of Chronic Obstructive Pulmonary Disease
ClinicalTrials.gov study NCT03240315. IPD Sharing: NO. Countries: 1. Publications: 2.
AI-driven Narrow-band Imaging Score for Disease Assessment and Outcome Prediction in Ulcerative Colitis
ClinicalTrials.gov study NCT06709209. IPD Sharing: NO. Countries: 6. Publications: 10.
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.