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ShareScore release 0.7.1
Dataset results
106 results for “Classification model”
Data from: Quantifying and modelling decay in forecast proficiency indicates the limits of transferability in land-cover classification
Open the record for dataset details and reuse information.
Comparison of DNA Methylation Based Classification Models for Precision Diagnostics of Central Nervous System Tumors
GEO Series GSE276299. Homo sapiens. 950 samples. Type: Methylation profiling by genome tiling array.
Molecular and spatial transcriptomic classification of midbrain dopamine neurons and their alterations in a LRRK2G2019S model of Parkinson’s disease
GEO Series GSE271781. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Deep Learning-Based Multimodal Clustering Model for Endotyping and Post-Arthroplasty Response Classification using Knee Osteoarthritis Subject-Matched Multi-Omic Data
GEO Series GSE222979. Homo sapiens. 1242 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Development and validation of a gene-based classification model for pN2 lung adenocarcinoma
GEO Series GSE282774. Homo sapiens. 58 samples. Type: Expression profiling by high throughput sequencing.
A comparison of model-based and model-free agents in solving semi-automatically generated PPDDL problems - Agent classification table
<p>This table classifies the agents used in the work to those which use models in their decision-making, which are model-based (MB), and those which do not, which are model-free (MF).</p>
Subfield classification model
<p>Web of Science Data of the Brazilian Physics publication in 2000-2019 used in the subfield classification model</p>
Radiomics Model Based on DCE-MRI and Ultrasound Images for Breast Lesion Classification
ClinicalTrials.gov study NCT06497023. IPD Sharing: NO. Countries: 1. Publications: 0.
Early Warning and Classification Model for Acute Non-traumatic Chest Pain
ClinicalTrials.gov study NCT06196307. IPD Sharing: NO. Countries: 1. Publications: 0.
Proteogenomics for Follicular Cell-derived Thyroid Cancer: Development of a Classification and Prognosis Prediction Model
ClinicalTrials.gov study NCT06969768. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Establishment of a Classification System and Postoperative Risk Warning Model for Patients Undergoing Bariatric Metabolic Surgery for Severe Obesity
ClinicalTrials.gov study NCT07093502. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Deep Learning Model for Pure Solid Nodules Classification
ClinicalTrials.gov study NCT05542992. IPD Sharing: NO. Countries: 1. Publications: 0.
Diagnostic Performance of an AI-based Model for TCM Constitution Classification Using Ophthalmic Imaging
ClinicalTrials.gov study NCT07127939. IPD Sharing: NO. Countries: 1. Publications: 0.
Implementation of the International Classification of Functioning, Disability and Health Model in Paediatric Cochlear Implant Recipients
ClinicalTrials.gov study NCT06841900. IPD Sharing: NO. Countries: 6. Publications: 0.
Development of an Artificial Intelligence-Based Model for Predicting Difficult Intubation Using Video Laryngoscopic Images and Cormack-Lehane Classification
ClinicalTrials.gov study NCT07152093. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Frailty Assessment Reveals Cognitive Differences in ASA Classification: Anesthesiologists vs Large Language Models
ClinicalTrials.gov study NCT07399938. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Dementia subtype prediction models constructed by penalized regression methods for multiclass classification using serum microRNA expression data
GEO Series GSE167559. Homo sapiens. 84 samples. Type: Expression profiling by array.
Transcriptomic Classification of Genetically Engineered Mouse Models of Breast Carcinoma Identifies Human Subtype Counterparts
GEO Series GSE42640. Mus musculus. 110 samples. Type: Expression profiling by array.
HER2 data used in the article entitled "MSclassifier: Median-Supplement model-based Classification tool for automated knowledge discovery"
<p>This repository contains HER2 training and test sets used for evaluating MSclassifier and other packages in the software article entitled "MSclassifier: median-supplement model-based classification tool for automated knowledge discovery." The training set is comprised of 100 instances and 74 attributes while the test set is comprised of 62 instances and 74 attributes. The training samples were used to obtain results from a 10-fold cross-validation testing of how MSclassifier and other packages accurately predicted HER2-receptor status phenotypes in breast cancer in the article. The data used in the software article was obtained from the supplementary data of "Adabor ES, Acquaah-Mensah GK, Machine learning approaches to decipher hormone and HER2 receptor status phenotypes in breast cancer, Briefings in Bioinformatics 2019; 20 (2): 504–514, https://doi.org/10.1093/bib/bbx138" by permission of Oxford University Press. Here, it is reproduced by permission of Oxford University Press.</p> <p> </p>
Faceted music: towards a model of music classification
<p>The organization of music is a subject that has fascinated classification researchers and librarians alike for over a hundred years. This paper identifies five key methodological approaches undertaken by commentators on music knowledge organization, which<br> demonstrate different interdependent relationships between musicology and classification. Five significant themes form the main body of this paper, and these themes underpin the corpus of music classification literature. The first theme concerns the question of whether classification should divide music materials into their constituent formats. This division sets conceptual against practical. The second theme looks at facets in music classification. ‘Medium’ and ‘form’ are considered to be the most important facets for music scores; ‘composers’ are an important facet for music literature. The third theme considers the poor treatment of ‘other’ musics in knowledge organization, and notes some possible explanations. The fourth theme investigates the relationship between the classification and retrieval of music materials. This section highlights the differing needs of users and suggests how the classification of music materials is adapted accordingly. The fifth theme discusses pre-existing music classification schemes, with the large number of home-grown and special schemes highlighted. <br> The paper concludes that the five identified themes point towards a model of music classification. However, the model is not just concerned with facets, musics and formats; it is also based upon the relationships between various sets of protagonists, such as the<br> librarian and the musicologist, the musicologist and the performer. Through studying these protagonists, the traditional boundaries of musicology, music librarianship and knowledge organization will be crossed.</p>
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.