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Bridging Machine Learning and Clinical Endpoints: A METABRIC-Informed Simulation Study of Missing Data Imputation for RECIST-Based Best Overall Response.

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Title: Bridging Machine Learning and Clinical Endpoints: A METABRIC-Informed Simulation Study of Missing Data Imputation for RECIST-Based Best Overall Response.
Authors: Tan, Fangya1 (AUTHOR), Long, Bowen1 (AUTHOR) blong@alumni.harrisburgu.edu
Source: Diagnostics (2075-4418). Jun2026, Vol. 16 Issue 12, p1853. 23p.
Database: Academic Search Ultimate
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  Data: Bridging Machine Learning and Clinical Endpoints: A METABRIC-Informed Simulation Study of Missing Data Imputation for RECIST-Based Best Overall Response.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=194906768
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        Value: 10.3390/diagnostics16121853
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        Text: English
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        PageCount: 23
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      – TitleFull: Bridging Machine Learning and Clinical Endpoints: A METABRIC-Informed Simulation Study of Missing Data Imputation for RECIST-Based Best Overall Response.
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              Text: Jun2026
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              Y: 2026
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