title: Heterogeneous data fusion for brain tumor classification.
abstract: 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 report, we present a novel machine learning framework for brain tumor             classification based on heterogeneous data fusion of metabolic and molecular datasets,             including state-of-the-art high-resolution magic angle spinning (HRMAS) proton             (1H) magnetic resonance spectroscopy and gene transcriptome profiling, obtained             from intact brain tumor biopsies. Our experimental results show that our novel             framework outperforms any analysis using individual dataset.
authors: Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA. vmetsis@uta.edu
authors: Vangelis
authors: V
authors: Metsis
authors: Heng
authors: H
authors: Huang
authors: Ovidiu C
authors: OC
authors: Andronesi
authors: Fillia
authors: F
authors: Makedon
authors: Aria
authors: A
authors: Tzika
mesh_terms: D000230:Adenocarcinoma / Q000145:classification / Q000175:diagnosis / Q000235:genetics / Q000473:pathology; D001185:Artificial Intelligence; D001254:Astrocytoma / Q000145:classification / Q000175:diagnosis / Q000235:genetics / Q000473:pathology; D001706:Biopsy; D001932:Brain Neoplasms / Q000145:classification* / Q000175:diagnosis / Q000473:pathology; D016022:Case-Control Studies; D004827:Epilepsy / Q000473:pathology / Q000601:surgery; D020869:Gene Expression Profiling / Q000145:classification; D015972:Gene Expression Regulation, Neoplastic; D005909:Glioblastoma / Q000145:classification / Q000175:diagnosis / Q000235:genetics / Q000473:pathology; D006801:Humans; D007177:Inappropriate ADH Syndrome / Q000145:classification / Q000175:diagnosis / Q000473:pathology; D009682:Magnetic Resonance Spectroscopy / Q000379:methods; D008579:Meningioma / Q000145:classification / Q000175:diagnosis / Q000235:genetics / Q000473:pathology; D012016:Reference Values