Investigators at German Cancer Research Center (DKFZ) Detail Findings in Machine Learning (Reproducible Radiomics Features From Multi-mri-scanner Test-retest-st udy: Influence On Performance and Generalizability of Models)
Investigators at German Cancer Research Center (DKFZ) Detail Findings in Machine Learning (Reproducible Radiomics Features From Multi-mri-scanner Test-retest-st udy: Influence On Performance and Generalizability of Models)
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Machine Learning. According to news reporting from Heidelberg, Germany, by NewsR x journalists, research stated, “Radiomics models trained on data from one cente r typically show a decline of performance when applied to data from external cen ters, hindering their introduction into large-scale clinical practice. Current e xpert recommendations suggest to use only reproducible radiomics features isolat ed by multiscanner test-retest experiments, which might help to overcome the pro blem of limited generalizability to external data.”
Key words
Heidelberg/Germany/Europe/B-Lymphocyt es/Blood Cells/Cyborgs/Emerging Technologies/Health and Medicine/Hemic and Immune Systems/Immune System/Immunology/Leukocytes/Machine Learning/Plasma Cells/German Cancer Research Center (DKFZ)
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