首页|University of Tunku Abdul Rahman Reports Findings in Personalized Medicine (Iden tifying miRNA as biomarker for breast cancer subtyping using association rule)
University of Tunku Abdul Rahman Reports Findings in Personalized Medicine (Iden tifying miRNA as biomarker for breast cancer subtyping using association rule)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Drugs and Therapies - Personalized Medicine is the subject of a report. According to news reporting ou t of Selangor, Malaysia, by NewsRx editors, research stated, "- This paper prese nts a comprehensive study focused on breast cancer subtyping, utilizing a multif aceted approach that integrates feature selection, machine learning classifiers, and miRNA regulatory networks. The feature selection process begins with the CF S algorithm, followed by the Apriori algorithm for association rule generation, resulting in the identification of significant features tailored to Luminal A, L uminal B, HER-2 enriched, and Basal-like subtypes." Our news journalists obtained a quote from the research from the University of T unku Abdul Rahman, "The subsequent application of Random Forest (RF) and Support Vector Machine (SVM) classifiers yielded promising results, with the SVM model achieving an overall accuracy of 76.60 % and the RF model demonstr ating robust performance at 80.85 %. Detailed accuracy metrics reve aled strengths and areas for refinement, emphasizing the potential for optimizin g subtype-specific recall. To explore the regulatory landscape in depth, an anal ysis of selected miRNAs was conducted using MIENTURNET, a tool for visualizing m iRNA-target interactions. While FDR analysis raised concerns for HER-2 and Basal -like subtypes, Luminal A and Luminal B subtypes showcased significant miRNA-gen e interactions. Functional enrichment analysis for Luminal A highlighted the rol e of Ovarian steroidogenesis, implicating specific miRNAs such as hsa-let-7c-5p and hsa-miR-125b-5p as potential diagnostic biomarkers and regulators of Luminal A breast cancer. Luminal B analysis uncovered associations with the MAPK signal ing pathway, with miRNAs like hsa-miR-203a-3p and hsa-miR-19a-3p exhibiting pote ntial diagnostic and therapeutic significance."
SelangorMalaysiaAsiaBiomarkersBr east CancerCancerCyborgsDiagnostics and ScreeningDrugs and TherapiesEm erging TechnologiesHealth and MedicineMachine LearningOncologyPersonaliz ed MedicinePersonalized TherapyWomen's Health
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