{"id":3469,"date":"2023-08-31T11:12:59","date_gmt":"2023-08-31T11:12:59","guid":{"rendered":"https:\/\/neuraldesigner.com\/learning\/breast-cancer-mortality-simulator\/"},"modified":"2025-08-26T11:04:59","modified_gmt":"2025-08-26T09:04:59","slug":"breast-cancer-mortality-simulator","status":"publish","type":"learning","link":"https:\/\/www.neuraldesigner.com\/learning\/examples\/breast-cancer-mortality-simulator\/","title":{"rendered":"Breast cancer mortality prediction machine learning simulator"},"content":{"rendered":"\t\t
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<\/p>\n

We have created a machine learning model to evaluate the mortality in breast cancer patients.<\/span><\/p>\n

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This model uses clinical, expresion and mutational data from almost two thousands of breast cancer patients, as described in Breast cancer mortality prediction using machine learning<\/a>.<\/p>\n

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Patient’s data:<\/h2>\n

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Chemotherapy:<\/td>\n
Hormone therapy:<\/td>\n
ER status measured by IHC:<\/td>\n
Neoplasm histologic grade:<\/td>\n
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HER status measured by SNP6:<\/td>\n
Lymph nodes examined positive:<\/td>\n
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Tumor size:<\/td>\n
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Tumor stage:<\/td>\n
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BARD1 expression:<\/td>\n
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MLH1 expression:<\/td>\n
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MSH6 expression:<\/td>\n
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CCNE1 expression:<\/td>\n
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CDK2 expression:<\/td>\n
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CDC25A expression:<\/td>\n
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CCND1 expression:<\/td>\n
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CDK6 expression:<\/td>\n
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SRC expression:<\/td>\n\n


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STAT1 expression:<\/td>\n\n


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STAT5B expression:<\/td>\n\n


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ADAM17 expression:<\/td>\n\n


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CIR1 expression:<\/td>\n\n


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DLL3 expression:<\/td>\n\n


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DTX3 expression:<\/td>\n\n


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KDM5A expression:<\/td>\n\n


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NOTCH1 expression:<\/td>\n\n


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PSEN2 expression:<\/td>\n\n


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HEY2 expression:<\/td>\n\n


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AURKA expression:<\/td>\n\n


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BMPR1B expression:<\/td>\n\n


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BRAF expression:<\/td>\n\n


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CASP10 expression:<\/td>\n\n


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CHEK1 expression:<\/td>\n\n


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MMP12 expression:<\/td>\n\n


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MMP7 expression:<\/td>\n\n


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MMP9 expression:<\/td>\n\n


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NFKB1 expression:<\/td>\n\n


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PDGFB expression:<\/td>\n\n


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RHEB expression:<\/td>\n\n


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RPS6KB2 expression:<\/td>\n\n


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SLC19A1 expression:<\/td>\n\n


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SMAD6 expression:<\/td>\n\n


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GATA3 expression:<\/td>\n\n


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RUNX1 expression:<\/td>\n\n


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TBX3 expression:<\/td>\n\n


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ABCC10 expression:<\/td>\n\n


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MAP2 expression:<\/td>\n\n


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MAPT expression:<\/td>\n\n


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TUBB4B expression:<\/td>\n\n


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AHNAK expression:<\/td>\n\n


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ARID2 expression:<\/td>\n\n


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CHD1 expression:<\/td>\n\n


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FANCD2 expression:<\/td>\n\n


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FLT3 expression:<\/td>\n\n


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LAMA2 expression:<\/td>\n\n


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NACOA3 expression:<\/td>\n\n


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NEK1 expression:<\/td>\n\n


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NR3C1 expression:<\/td>\n\n


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NRAS expression:<\/td>\n\n


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PRKCQ expression:<\/td>\n\n


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RPGR expression:<\/td>\n\n


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SIAH1 expression:<\/td>\n\n


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AR expression:<\/td>\n\n


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CYP21A2 expression:<\/td>\n\n


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SRD5A3 expression:<\/td>\n\n


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TP53 mutated:<\/td>\n
Overall mortality:<\/b><\/td>\n6.74%<\/b><\/output><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/form>\n<\/div>\n