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In this work, a combination model based on two well-known concepts (fuzzy systems and support vector regression) has been developed to create a predictor for relapse time of breast cancer. The most important feature of this work is to propose a method for gene selection as well as fuzzy rul...
A linear support vector machine (SVM) is used to extract 6 fea- tures from a total of 31 features in a dataset of 253 breast cancer patients. Five features are nuclear features obtained during a non-invasive diagnostic procedure while one feature, tumor size, is obtained during surgery. The...
When the network is shown an image, this layer produces a 512D vector of real numbers, the tissue fingerprint. In the remainder of the work, we apply the network to extract fingerprints and explore how they can be used to link histologic patterns to clinical subgroups of breast cancer. ...
Early life environmental exposures affect breast development and breast cancer risk in adulthood. The breast is particularly vulnerable during puberty when mammary epithelial cells proliferate exponentially. In overweight/obese (OB) women, inflammation increases breast aromatase expression and estrogen synthesis...
Breast cancer (BC), as one of the leading causes of death among women, comprises several subtypes with controversial and poor prognosis. Considering the TNM (tumor, lymph node, metastasis) based classification for staging of breast cancer, it is essential to diagnose the disease at early stages...
D. Immunoblot showing expression of WHSC1L1-short and ERα in three breast cancer cell lines following transduction with a lentiviral expression vector for the short isoform of WHSC1L1. E. MCF-7 (left) or SUM-44 (right) cells were transfected with either LacZ or three different ESR1 shRNAs...
In breast cancer, prolactin-induced activation of the transcription factor STAT5a results from the phosphorylation of STAT5a tyrosine residue 694. However, its role in mammary oncogenesis remains an unsettled debate as STAT5a exhibits functional dichotom