INTRODUCTION Studies of triple-negative breast cancer have recently been extending the inclusion criteria and incorporating additional molecular markers into the selection criteria, opening up scope for targeted therapies. The screening phases required for studies of this type are often prolonged, since the process of determining the molecular subtype and carrying out additional biomarker asses...

introduction: the adaptive neuro-fuzzy inference system (anfis) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. in this study we used this model in breast cancer detection. methodology: a set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used.  first, the risk fact...

conclusions expression of armc3 in tumor samples and normal adjacent tissue is very important. the expression of this gene in tumor-adjacent tissue may be associated with the stage of cancer; it may be that these tissues are affected by epigenetic and oncogenic changes of breast cancer. accordingly, aberrant expression of armc3 in tumor samples may be an attractive candidate for use as a tumor ...

background: idiopathic granulomatous mastitis (igm) is a rare benign breast disease, which can mimic breast cancer. as the managements of igm and breast cancer are entirely different and the initial clinical manifestations are similar in several cases, it is very important to differentiate them. case presentation: we reported a 48-year-old female patient with igm and breast cancer. she was refe...

background: potential association of leptin (lep) gene polymorphisms has been suggested in the processes leading to breast cancer initiation and progression. we investigated whether genetic variations in the lep -2548g/a gene are associated with risk of breast cancer. methods: this case-control study consisted of 100 breast cancer cases and 100 control subjects without breast cancer that matche...

Risk prediction algorithms are an important tool for identifying individuals at high risk of developing the disease who can then be offered individually tailored clinical management. Several algorithms that predict the probability of breast cancer incidence are currently used in clinical practice. It is uncertain, though, as to which of the breast cancer risk prediction models performs best for...

BACKGROUND Comprehensive understanding of intratumor heterogeneity requires identification of molecular markers, which are capable of differentiating different subpopulations and which also have clinical significance. One important tool that has been addressing this issue is single cell RNA-Sequencing (scRNASeq) that allows the quantification of expression profiles of transcripts in individual ...

MOTIVATION Metastasis prediction is a well-known problem in breast cancer research. As breast cancer is a complex and heterogeneous disease with many molecular subtypes, predictive models trained for one cohort often perform poorly on other cohorts, and a combined model may be suboptimal for individual patients. Furthermore, attempting to develop subtype-specific models is hindered by the ambig...

Background: Breast cancer incidence has increased rapidly inKuwait, but there haven’t been any studies investigating the recognized risk factors of breast cancer inKuwait. The aim of the study was to investigate breast cancer risk factors among women inKuwait. Methods: A case-control study was conducted in Kuwait from May 2003 to March 2004 using a questionnaire including socio-demographic data...