Heterogeneous Data Fusion to Type Brain Tumor Biopsies [chapter]

Vangelis Metsis, Heng Huang, Fillia Makedon, Aria Tzika
2009 IFIP Advances in Information and Communication Technology  
Current research in biomedical informatics involves analysis of multiple heterogeneous data sets. This includes patient demographics, clinical and pathology data, treatment history, patient outcomes as well as gene expression, DNA sequences and other information sources such as gene ontology. Analysis of these data sets could lead to better disease diagnosis, prognosis, treatment and drug discovery. In this paper, we use machine learning algorithms to create a novel framework to perform the
more » ... rogeneous data fusion on both metabolic and molecular datasets, including state-of-the-art high-resolution magic angle spinning (HRMAS) proton (1H) Magnetic Resonance Spectroscopy and gene transcriptome profiling, to intact brain tumor biopsies and to identify different profiles of brain tumors. Our experimental results show our novel framework outperforms any analysis using individual dataset.
doi:10.1007/978-1-4419-0221-4_28 fatcat:i5yhlkv5prejtd5np5sdjduhli