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Reproducibility of radiomic features using network analysis and its application in Wasserstein k-means clustering

Journal of Medical Imaging(2021)10.1117/1.jmi.8.3.031904Source: DataRank Database

Reproducibility of radiomic features using network analysis and its application in Wasserstein k-means clustering is a research paper published in Journal of Medical Imaging (2021). On theSindex it has a DataRank of 0. It has been cited 6 times.

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Open Access6 citations

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Enrichment:Funding (8 grants)Impact (FWCI 0.25)OA: hybridTopics (30)IDs (PubMed, PMC, OpenAlex)Annotations (1)SDGs (2)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (14)

Aditya Apte ORCID,Evangelia Katsoulakis ORCID,Nadeem Riaz ORCID,Vaios Hatzoglou ORCID,Yao Yu ORCID

Live enrichment

PubMed:33954225 PMC:PMC8085581 OpenAlex:https://openalex.org/W3158273161

National Institutes of Health

Grant: R21 CA234752

National Institutes of Health

Grant: R01-AG048769

Air Force Office of Scientific Research

Grant: FA9550-20-1-0029

National Institutes of Health

Grant: P30 CA008748

NIA NIH HHS

Grant: R01 AG048769

National Institutes of Health

Grant: 2P30CA008748-43

MOUSE GENETICS

National Institutes of Health

Grant: 5R21CA234752-02

Radiotherapy-associated breast cancer: machine learning on genotypes to predict individualized risk

National Institutes of Health

Grant: 5R01AG048769-04

Glymphatic function in a transgenic rat model of Alzheimer's disease

FWCI

0.25

Citation Percentile

0.5%

Citation Trend

2022

2024

2025

2026

hybridLicense: cc-by

journalhttps://www.spiedigitallibrary.org/journals/journal-of-medical-imaging/volume-8/issue-3/031904/Reproducibility-of-radiomic-features-using-network-analysis-and-its-application/10.1117/1.JMI.8.3.031904.pdf

publisherhttps://www.spiedigitallibrary.org/journals/journal-of-medical-imaging/volume-8/issue-3/031904/Reproducibility-of-radiomic-features-using-network-analysis-and-its-application/10.1117/1.JMI.8.3.031904.pdf

publisherhttps://www.spiedigitallibrary.org/journalArticle/Download?urlId=10.1117%2F1.JMI.8.3.031904

journalhttps://doi.org/10.1117/1.jmi.8.3.031904

repositoryhttps://pubmed.ncbi.nlm.nih.gov/33954225

Fields of Study

Radiomics and Machine Learning in Medical ImagingMRI in cancer diagnosisEsophageal Cancer Research and Treatment0301 basic medicine03 medical and health sciences0302 clinical medicine

Keywords

Cluster analysisReproducibilityImaging phantomReliability (semiconductor)Head and neck squamous-cell carcinomaMedicinePattern recognition (psychology)Data setData miningFeature (linguistics)Set (abstract data type)Lung cancerArtificial intelligenceComputer scienceCancerNuclear medicineHead and neck cancerMathematicsStatisticsPathologyRadiomicsWasserstein DistanceNetwork-based Wasserstein K-means ClusteringSpecial Section on Radiogenomics in Prognosis and Treatment

Sustainable Development Goals

SDG 3: 3. Good healthSDG 0: Good health and well-being

Reproducibility of radiomic features using network analysis and its application in Wasserstein k-means clustering

FAIR Checklist

Authors (14)

Funding (8 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)