jmp genomics sas-based software (SAS institute)
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SAS institute
jmp genomics sas-based software
Jmp Genomics Sas Based Software, supplied by SAS institute, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/jmp+genomics+sas-based+software/jmp+genomics/us12365948-94-25-27
Average 90 stars, based on 1 article reviews
Jmp Genomics Sas Based Software, supplied by SAS institute, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/jmp+genomics+sas-based+software/jmp+genomics/us12365948-94-25-27
Average 90 stars, based on 1 article reviews
jmp genomics sas-based software - by Bioz Stars,
2026-09
90/100 stars
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Gene Expression:Article Title: Diagnostic test for predicting metastasis and recurrence in cutaneous melanoma Article Snippet: Various linear and non-linear predictive modeling methods, including radial basis machine, k-nearest neighbor, partition tree, logistic regression, discriminant analysis and distance scoring, were performed using Article Title: Diagnostic test for predicting metastasis and recurrence in cutaneous melanoma Article Snippet: Various linear and non-linear predictive modeling methods, including radial basis machine, k-nearest neighbor, partition tree, logistic regression, discriminant analysis and distance scoring, were performed using Article Title: Analytic validity of DecisionDx-Melanoma, a gene expression profile test for determining metastatic risk in melanoma patients Article Snippet: Steps in the performance of the test are presented along with the corresponding reliability analyses Resulting standardized ΔCt values for each test sample were analyzed with a radial basis machine (RBM) predictive model from a validated training set of 164 melanoma cases with known metastatic outcomes [ ] using Article Title: Identification of high-risk cutaneous melanoma tumors is improved when combining the online American Joint Committee on Cancer Individualized Melanoma Patient Outcome Prediction Tool with a 31-gene expression profile-based classification. Article Snippet: Radial basis machine predictive modeling with Control:Article Title: Diagnostic test for predicting metastasis and recurrence in cutaneous melanoma Article Snippet: Various linear and non-linear predictive modeling methods, including radial basis machine, k-nearest neighbor, partition tree, logistic regression, discriminant analysis and distance scoring, were performed using Article Title: Diagnostic test for predicting metastasis and recurrence in cutaneous melanoma Article Snippet: Various linear and non-linear predictive modeling methods, including radial basis machine, k-nearest neighbor, partition tree, logistic regression, discriminant analysis and distance scoring, were performed using Article Title: Analytic validity of DecisionDx-Melanoma, a gene expression profile test for determining metastatic risk in melanoma patients Article Snippet: Steps in the performance of the test are presented along with the corresponding reliability analyses Resulting standardized ΔCt values for each test sample were analyzed with a radial basis machine (RBM) predictive model from a validated training set of 164 melanoma cases with known metastatic outcomes [ ] using Article Title: Identification of high-risk cutaneous melanoma tumors is improved when combining the online American Joint Committee on Cancer Individualized Melanoma Patient Outcome Prediction Tool with a 31-gene expression profile-based classification. Article Snippet: Radial basis machine predictive modeling with |