Predicting HER2 Status Associated with Breast Cancer Aggressiveness Using Four Machine Learning Models.

Objective: Breast cancer (BC) is a heterogeneous disease with various biological and clinical subtypes. HER2 status (human epidermal growth factor receptor 2) is a crucial biomarker, associated with aggressive tumor behavior and poor prognosis. Advanced algorithmic models can aid in predicting cancer growth and metastasis, serving as valuable clinical tools for classification and treatment.

SNPs-Panel Polymorphism Variations in and Genes Are Not Associated with Prostate Cancer.

Prostate cancer (PCa) is a major public health problem worldwide. Recent studies have suggested that ghrelin and its receptor could be involved in the susceptibility to several cancers such as PCa, leading to their use as an important predictive way for the clinical progression and prognosis of cancer. However, conflicting results of single nucleotide polymorphisms (SNPs) with ghrelin () and its receptor () genes were demonstrated in different studies.