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356
datasets available to search
ShareScore release 0.9.0
Dataset results
356 results for “Machine learning models”
A Machine Learning Prediction Model for Delayed CIPONV
ClinicalTrials.gov study NCT06443697. IPD Sharing: NO. Countries: 1. Publications: 9.
Clinical Prediction Models for Pediatric In-Hospital Death Risk in Congolese Severe Malaria Children Using Machine Learning Based-Algorithms
ClinicalTrials.gov study NCT07355426. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
Machine Learning Model for Perioperative Transfusion Prediction
ClinicalTrials.gov study NCT05228548. IPD Sharing: NO. Countries: 1. Publications: 3.
Machine Learning Models for Prediction of Acute Kidney Injury After Noncardiac Surgery
ClinicalTrials.gov study NCT06146829. IPD Sharing: NO. Countries: 1. Publications: 1.
To Construct a Prognosis Prediction Model for ECMO Patients Based on Machine Learning Algorithms
ClinicalTrials.gov study NCT06654388. IPD Sharing: NO. Countries: 1. Publications: 2.
Development of Machine Learning Models to Predict Postoperative GERD Symptom Resolution After Laparoscopic Nissen Fundoplication
ClinicalTrials.gov study NCT06862037. IPD Sharing: NO. Countries: 1. Publications: 6.
Machine Learning Model to Predict HOLS and Mortality After Discharge in Hospitalized Oncologic Patients
ClinicalTrials.gov study NCT05534178. IPD Sharing: YES. Countries: 1. Publications: 5.
A Multicenter Study on Early Diagnosis of NSTE-ACS Patients Based on Machine Learning Model
ClinicalTrials.gov study NCT04682756. IPD Sharing: UNDECIDED. Countries: 1. Publications: 15.
Artificial Intelligence-Based Machine Learning to Diagnose and Classify Adenomyosis from Ultrasound Scans: a Multicentre Model Development Study
ClinicalTrials.gov study NCT06765512. IPD Sharing: NO. Countries: 1. Publications: 19.
Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care: Study 2
ClinicalTrials.gov study NCT06646133. IPD Sharing: YES. Countries: 1. Publications: 6.
A1Check: the External Validation of a Machine Learning Model Predicting Colorectal Anastomotic Leakage
ClinicalTrials.gov study NCT05810207. IPD Sharing: YES. Countries: 1. Publications: 15.
Development of a Machine Learning Model for Nasopharyngeal Carcinoma Screening Based on Tongue Imaging
ClinicalTrials.gov study NCT06129201. IPD Sharing: UNDECIDED. Countries: 1. Publications: 16.
Prediction model of in-hospital mortality in intensive care unit patients with heart failure: machine learning-based, retrospective analysis of the MIMIC-III database
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Code for: Comparison and interpretability of machine learning models to predict severity of chest injury
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Systematic review of validation of supervised machine learning models in accelerometer-based animal behaviour classification literature
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Benchmarking parametric and machine learning models for genomic prediction of complex traits
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Calibration of probability predictions from machine-learning and statistical models
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Development and validation of a machine learning model for use as an automated artificial intelligence tool to predict mortality risk in patients with COVID-19
<p><strong>Background</strong></p> <p>New York City quickly became an epicenter of the COVID-19 pandemic. Due to a sudden and massive increase in patients during COVID-19 pandemic, healthcare providers incurred an exponential increase in workload which created a strain on the staff and limited resources. As this is a new infection, predictors of morbidity and mortality are not well characterized.</p> <p><strong>Methods</strong></p> <p>We developed a prediction model to predict patients at risk for mortality using only laboratory, vital and demographic information readily available in the electronic health record on more than 3000 hospital admissions with COVID-19. A variable importance algorithm was used for interpretability and understanding of performance and predictors.</p> <p><strong>Findings</strong></p> <p>We built a model with 84-97% accuracy to identify predictors and patients with high risk of mortality, and developed an automated artificial intelligence (AI) notification tool that does not require manual calculation by the busy clinician. Oximetry, respirations, blood urea nitrogen, lymphocyte percent, calcium, troponin and neutrophil percentage were important features and key ranges were identified that contributed to a 50% increase in patients’ mortality prediction score. With an increasing negative predictive value (NPV) starting 0.90 after the second day of admission, we are able more confidently able identify likely survivors. This study serves as a use case of a model with visualizations to aide clinicians with a better understanding of the model and predictors of mortality. Additionally, an example of the operationalization of the model via an AI notification tool is illustrated.</p>
Machine learning based root stress calculation model for gears with progressive curved path of contact
<p><em>A machine learning based model for calculation of root stress in gears with a progressive curved path of contact is proposed. The prediction model is used as a surrogate model to the finite element analysis simulations, from which the data was collected. The results of the validation of all the methods are presented. Further validation was done with new simulations.</em></p>
Data and R code for cluster analysis and machine learning modelling of favourite places for outdoor recreation
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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.