{ "_id": "6ad608e86b811b735aabe2d3", "Package": "CPSM", "Type": "Package", "Title": "CPSM: Cancer patient survival model", "Version": "1.5.0", "Authors@R": "c(person(\"Harpreet\", \"Kaur\", email = \"hks04180@gmail.com\", \nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-0421-8341\")),\nperson(\"Pijush\", \"Das\", email = \"topijush@gmail.com\",\nrole = c(\"aut\")),\nperson(\"Kevin\", \"Camphausen\", email = \"camphauk@mail.nih.gov\",\nrole = c(\"aut\")),\nperson(\"Uma\", \"Shankavaram\" , email = \"uma@mail.nih.gov\",\nrole = c(\"aut\", \"ctb\")))", "Description": "CPSM provides a comprehensive computational pipeline for\npredicting survival probability and risk groups in cancer\npatients. The package includes steps for data preprocessing,\ntraining/test split, and normalization. It enables feature\nselection using univariate survival analysis and computes a\nLASSO-based prognostic index (PI) score. CPSM supports the\ndevelopment of predictive models using various feature sets and\noffers a suite of visualization tools, including survival\ncurves based on predicted probabilities, barplots for predicted\nmean and median survival times, KM plots overlaid with\nindividual survival predictions, and nomograms for estimating\n1-, 3-, 5-, and 10-year survival probabilities. 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