Rachel Ng, Ahmed Adam, Nathan Poppleton, Christopher Oldmeadow, Aniruddh V Deshpande
Lack of consensus in atypical congenital obstructive urethral lesions in children: Snapshot of the web-based ObsCUre (obstruction to the child urethra) study
Current urology
determining tumor origin humans vital clinical applications molecular diagnostics metastatic cancer usually aggressive disease limited diagnostic procedures despite fact many protocols evaluated effectiveness prognostication research shown dysregulation mirnas class noncoding regulatory rnas remarkably involved oncogenic conditions research paper aims develop machine learning model processes array mirnas 1097 metastatic tissue samples patients suffered various stages breast cancer suggested machine learning model fed mirna quantitative read count data taken cancer genome atlas data repository two main featureselection techniques used mainly neighborhood component analysis minimum redundancy maximum relevance identify discriminant relevant mirnas upregulated downregulated states mirnas validated biological identifiers four cancer stages breast tumors machine learning algorithms yield performance scores significantly higher traditional foldchange approach particularly earlier stages cancer neighborhood component analysis minimum redundancy maximum relevance achieving accuracy scores 0983 0931 respectively compared 0920 fc method study underscores potential advanced featureselection methods enhancing accuracy cancer stage identification paving way improved diagnostic therapeutic strategies oncology