Mini Review
In Cancer Precision Medicine, Deep Machine Learning Enables Multi-Data Type Processing And Prediction Biomarker Advancement
Author(s): Sanjiv Kumar*
Gene-environment interactions that change cellular homeostasis are associated with cancer progression. It is possible to significantly enhance diagnosis and treatment by using biomarkers as early indicators of illness appearance and development. Data-driven biomarker discoveries have been made possible by the large omics datasets produced by high-throughput profiling technologies like microarrays, RNA sequencing, whole-genome shotgun sequencing, nuclear magnetic resonance, and mass spectrometry. Traditionally, linear parametric modelling has been the only statistical technique used to identify features with differential expression as molecular markers. Oncogene heterogeneity, epigenetic alterations, and high levels of polymorphism necessitate biomarker-assisted, individualised treatment plans. In recent years, more and more research into numerous diseases has been conducted using deep.. View More»
DOI:
10.14303/irjbcs.2023.37