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  "Title": "Biomarker Optimal Segmentation System",
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  "Description": "The Biomarker Optimal Segmentation System R package,\n'bossR', is designed for precision medicine, helping to\nidentify individual traits using biomarkers. It focuses on\ndetermining the most effective cutoff value for a continuous\nbiomarker, which is crucial for categorizing patients into two\ngroups with distinctly different clinical outcomes. The package\nsimultaneously finds the optimal cutoff from given candidate\nvalues and tests its significance. Simulation studies\ndemonstrate that 'bossR' offers statistical power and false\npositive control non-inferior to the permutation approach\n(considered the gold standard in this field), while being\nhundreds of times faster.",
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    "Date": "2026-10-17 07:40:33 UTC",
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  "Author": "Liuyi Lan [aut], Xing Li [aut]\n(<https://orcid.org/0000-0002-4186-7909>), Xuanjin Cheng [aut],\nXuekui Zhang [aut, cre]\n(<https://orcid.org/0000-0003-4728-2343>)",
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  "Date/Publication": "2024-01-16 02:40:52 UTC",
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