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- W344722506 abstract "In this paper, we will try to predict the recurrence of melanoma in the subset ofpatients with a “thin melanoma,” defined by having a Breslow Thickness less than1.00mm. The study used the 1610 patient data base from the Duke Melanoma Clinic. Themethods used to try classifying these patients as to whether or not they will suffer arecurrence are based on the statistical processes of trees and random forests introduced byDr. L. Breiman. Successful results were achieved only when all patients were studiedincluding those with an advanced stage of disease, but who still qualified as patients witha thin melanoma by histological measurement. The variables collected on each patientand used in this study related to the Breslow Thickness, Clark level, initial stage, age,primary site of lesion, local pathological events, histological type, sex, race and previousimmunotherapy. The factors other than the initial stage and extent of disease proved tooweak to give any meaningful results when only patients with local disease were studied.The results using a single tree and a random forest were compared. A detailed discussionof trees and random forest with use in the R-2.01 CRAN software packages is included.Although the results of this study did not provide the answers for this specific set ofmelanoma patients, it is felt that the techniques and programs written would be applicablein a differently defined set of patients. The results could be an important step indetermining which patients should receive therapy and then evaluating the results of theadjuvant therapy on a more properly defined group of patients." @default.
- W344722506 created "2016-06-24" @default.
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- W344722506 date "2009-01-01" @default.
- W344722506 modified "2023-09-26" @default.
- W344722506 title "Prediction of recurrence in thin melanoma using trees and random forests" @default.
- W344722506 hasPublicationYear "2009" @default.
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