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radiomics-based random forest model  (Johns Hopkins HealthCare)

 
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    Johns Hopkins HealthCare radiomics-based random forest model
    Radiomics Based Random Forest Model, supplied by Johns Hopkins HealthCare, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/random+forest+algorithm+model/radiomics+based+random+forest+model/pm37173876-157-24-19
    Average 90 stars, based on 1 article reviews
    radiomics-based random forest model - by Bioz Stars, 2026-09
    90/100 stars

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    Related Articles

    other:

    Article Title: Artificial Intelligence in the Diagnosis and Treatment of Pancreatic Cystic Lesions and Adenocarcinoma
    Article Snippet: In a larger retrospective study including 214 patients who underwent resection for pancreatic cysts at Johns Hopkins, the radiomics-based random forest model yielded an AUC of 0.940 for distinguishing between five types of cystic neoplasms (IPMNs, MCNs, SPNs, SCAs, and cystic NETs) [ ].

    Imaging:

    Article Title: Artificial Intelligence in the Diagnosis and Treatment of Pancreatic Cystic Lesions and Adenocarcinoma.
    Article Snippet: .. Cross-Sectional Imaging in PCLs In a larger retrospective study including 214 patients who underwent resection for pancreatic cysts at Johns Hopkins, the radiomics-based random forest model yielded an AUC of 0.940 for distinguishing between five types of cystic neoplasms (IPMNs, MCNs, SPNs, SCAs, and cystic NETs) [57]. ..



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