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pubmed-article:16865598pubmed:abstractTextCurrently, approximately 80% of melanoma patients undergoing sentinel node biopsy (SNB) have negative sentinel lymph nodes (SLNs), and no prediction system is reliable enough to be implemented in the clinical setting to reduce the number of SNB procedures. In this study, the predictive power of support vector machine (SVM)-based statistical analysis was tested.lld:pubmed
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pubmed-article:16865598pubmed:articleTitleSupport vector machine learning model for the prediction of sentinel node status in patients with cutaneous melanoma.lld:pubmed
pubmed-article:16865598pubmed:affiliationClinica Chirurgica 2, Dipartimento di Scienze Oncologiche e Chirurgiche, Università di Padova, Via Giustiniani, 2, 35128 Padova, Italy. mocellins@hotmail.comlld:pubmed
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pubmed-article:16865598pubmed:publicationTypeResearch Support, Non-U.S. Gov'tlld:pubmed
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